Efficacy and safety of PARP inhibitors in the treatment of prostatic cancer: a systematic review and network meta-analysis.

BACKGROUND: Prostate cancer (PCa) is the most common cancer and the second leading cause of cancer-related death in men. Previous studies have shown that the poly (adenosine diphosphate-ribose) polymerase (PARP) inhibitors (PARPis) improve the treatment response of patients with metastatic castration-resistant PCa (mCRPC). However, the efficacy and safety of various PARPis in mCRPC patients remain unclear, presenting a significant challenge for clinicians when making treatment decisions. To address this, this study conducted two indirect comparisons to evaluate the efficacy and safety of four PARPis (olaparib, niraparib, rucaparib, and talazoparib) in patients with mCRPC. METHODS: A systematic review and network meta-analysis (NMA) using Bayesian statistics was conducted. A comprehensive literature search was performed of the PubMed, Web of Science, Cochrane Library, Embase, and China National Knowledge Infrastructure (CNKI) databases to identify relevant studies from the inception to November 8, 2023, using search terms such as "PARP inhibitor", "olaparib", "rucaparib", "niraparib", "talazoparib", and "mCRPC". Phase 2/3 randomized controlled trials (RCTs) related to PARPi therapy and novel hormonal therapy in patients with mCRPC were included in the analysis. The targeted outcomes included radiographic progression-free survival (rPFS), overall survival (OS), adverse events (AEs), and grade ≥3 AEs. Four reviewers screened the titles and abstracts independently to assess the eligibility of each article. Two researchers independently extracted data from the included studies. The risk of bias and quality of the studies were assessed using the Risk-of-Bias 2 tool. RESULTS: Six high-quality phase 2/3 clinical trials, comprising 3,205 individuals, were selected for the systematic review and NMAs. Two NMAs were conducted due to the different designs of the six clinical trials. The indirect comparison with a random-effects model of olaparib, niraparib, and talazoparib showed that olaparib significantly improved rPFS with a hazard ratio (HR) of 0.67 [95% confidence interval (CI): 0.46-0.96]; however, no such significant difference was observed in relation to olaparib and rucaparib. In terms of OS, no significant difference was observed among olaparib, niraparib, and talazoparib. In relation to the AEs, the PARPi interventions using olaparib, niraparib, and talazoparib increased the rates of grade ≥3 AEs with odds ratios (ORs) of 2.0 (95% CI: 0.89-5.3), 3.0 (95% CI: 1.3-7.4), and 3.7 (95% CI: 1.1-12.0), respectively. In the rank probability analysis, according to the surface under the cumulative ranking (SUCRA), olaparib ranked first, followed by niraparib, and talazoparib. Most of the included studies were assessed to be at low risk of bias. CONCLUSIONS: Olaparib significantly improved rPFS among olaparib, niraparib, and talazoparib. Talazoparib exhibited the highest SUCRA value. Regarding safety, olaparib and rucaparib did not significantly increase the incidence of grade ≥3 AEs. When making personalized treatment decisions, clinicians should consider individual patient characteristics, treatment efficacy, and potential AEs.

The discriminatory capability of anthropometric measures in predicting reproductive outcomes in Chinese women with PCOS.

OBJECTIVE: Obesity is a common feature in women with polycystic ovary syndrome (PCOS) and potentially significantly influences reproductive function. However, opinions are divided as to which factor is a more appropriate obesity predictor of reproductive outcomes. The aim of this study was to investigate the discriminatory capability of anthropometric measures in predicting reproductive outcomes in Chinese women with PCOS. METHODS: A total of 998 women with PCOS from PCOSAct were included. Logistic regression models were used to compute the odds ratios (ORs) and 95% confidence interval (95% CIs) to assess the effect of anthropometric measures, including body mass index (BMI), waist circumference (WC), hip circumference (HC), the waist‒hip ratio (WHR) and the waist‒height ratio (WHtR), on reproductive outcomes. The discrimination abilities of the models were assessed and compared based on the area under the receiver operating characteristic curve (AUC), Akaike's information criterion (AIC) and integrated discrimination improvement (IDI). RESULTS: Among PCOS women, there was a graded association between anthropometric measures and predicted reproductive outcomes across quintiles of anthropometric measures, including a linear association among WHR, BMI and reproductive outcomes and among waist circumference, WHtR and live birth, pregnancy, and ovulation. However, only a linear association was noted between the hip and ovulation. C-statistic comparisons and IDI analyses revealed a trend towards a significant superiority of BMI for ovulation and WHR for live birth, pregnancy and conception in the models. Combining obesity variables improved discrimination in the multivariable models for reproductive outcomes. CONCLUSIONS: Our findings support that BMI is a better predictor of ovulation and that the WHR is a better predictor of live birth, pregnancy and conception, whereas the combination of obesity variables contributes to the discrimination of reproduction.

Multimodal Deep Learning Network for Differentiating Between Benign and Malignant Pulmonary Ground Glass Nodules.

OBJECTIVE: This study aimed to establish a multimodal deep-learning network model to enhance the diagnosis of benign and malignant pulmonary ground glass nodules [GGNs]. METHODS: Retrospective data on pulmonary GGNs were collected from multiple centers across China, including North, Northeast, Northwest, South, and Southwest China. The data were divided into a training set and a validation set in an 8:2 ratio. In addition, a GGN dataset was also obtained from our hospital database and used as the test set. All patients underwent chest computed tomography [CT], and the final diagnosis of the nodules was based on postoperative pathological reports. The Residual Network [ResNet] was used to extract imaging data, the Word2Vec method for semantic information extraction, and the Self Attention method for combining imaging features and patient data to construct a multimodal classification model. Then, the diagnostic efficiency of the proposed multimodal model was compared with that of existing ResNet and VGG models and radiologists. RESULTS: The multicenter dataset comprised 1020 GGNs, including 265 benign and 755 malignant nodules, and the test dataset comprised 204 GGNs, with 67 benign and 137 malignant nodules. In the validation set, the proposed multimodal model achieved an accuracy of 90.2%, a sensitivity of 96.6%, and a specificity of 75.0%, which surpassed that of the VGG [73.1%, 76.7%, and 66.5%] and ResNet [78.0%, 83.3%, and 65.8%] models in diagnosing benign and malignant nodules. In the test set, the multimodal model accurately diagnosed 125 [91.18%] malignant nodules, outperforming radiologists [80.37% accuracy]. Moreover, the multimodal model correctly identified 54 [accuracy, 80.70%] benign nodules, compared to radiologists' accuracy of 85.47%. The consistency test comparing radiologists' diagnostic results with the multimodal model's results in relation to postoperative pathology showed strong agreement, with the multimodal model demonstrating closer alignment with gold standard pathological findings [Kappa=0.720, P<0.01]. CONCLUSION: The multimodal deep learning network model exhibited promising diagnostic effectiveness in distinguishing benign and malignant GGNs and, therefore, holds potential as a reference tool to assist radiologists in improving the diagnostic accuracy of GGNs, potentially enhancing their work efficiency in clinical settings.

Promoting precision health using fitness wearable and apps among breast cancer survivors: Protocols of a smart health management trial.

BACKGROUND: Annually, approximately 1.7 million women are diagnosed with breast cancer worldwide. Engaging in regular physical activity (PA) post-diagnosis brings significant health benefits, enhancing breast cancer survivors' (BCS) prognosis and overall health-related quality of life (HRQoL). Despite these benefits, a low percentage of Chinese BCS adhere to the recommended moderate-to-vigorous PA levels. This highlights the need for innovative PA interventions tailored for BCS management. eHealth technology, such as fitness wearables and apps, presents an opportunity to improve BCS healthcare by offering personalized exercise programs. METHODS: This study focuses on developing a precision eHealth PA program for 200 Chinese BCS in Guangdong Province, using a custom micro-application and a smart band for a 12-month trial. All participants will receive a Huawei Smart Band and be divided into 1) a personalized intervention group, receiving daily PA tracking and feedback, and 2) a control group receiving standard care. The primary outcome is PA and secondary outcomes include biomarkers, weight and body composition, functional fitness, HRQoL, and individual beliefs. Outcomes will be assessed at baseline, 6 months, and 12 months (endpoint). Successful outcomes could revolutionize PA programs for Chinese BCS, providing a model for future eHealth interventions.

Automatically Detecting Pancreatic Cysts in Autosomal Dominant Polycystic Kidney Disease on MRI Using Deep Learning.

BACKGROUND: Pancreatic cysts in autosomal dominant polycystic kidney disease (ADPKD) correlate with PKD2 mutations, which have a different phenotype than PKD1 mutations. However, pancreatic cysts are commonly overlooked by radiologists. Here, we automate the detection of pancreatic cysts on abdominal MRI in ADPKD. METHODS: Eight nnU-Net-based segmentation models with 2D or 3D configuration and various loss functions were trained on positive-only or positive-and-negative datasets, comprising axial and coronal T2-weighted MR images from 254 scans on 146 ADPKD patients with pancreatic cysts labeled independently by two radiologists. Model performance was evaluated on test subjects unseen in training, comprising 40 internal, 40 external, and 23 test-retest reproducibility ADPKD patients. RESULTS: Two radiologists agreed on 52% of cysts labeled on training data, and 33%/25% on internal/external test datasets. The 2D model with a loss of combined dice similarity coefficient and cross-entropy trained with the dataset with both positive and negative cases produced an optimal dice score of 0.7 ± 0.5/0.8 ± 0.4 at the voxel level on internal/external validation and was thus used as the best-performing model. In the test-retest, the optimal model showed superior reproducibility (83% agreement between scan A and B) in segmenting pancreatic cysts compared to six expert observers (77% agreement). In the internal/external validation, the optimal model showed high specificity of 94%/100% but limited sensitivity of 20%/24%. CONCLUSIONS: Labeling pancreatic cysts on T2 images of the abdomen in patients with ADPKD is challenging, deep learning can help the automated detection of pancreatic cysts, and further image quality improvement is warranted.

A randomized prospective study comparing the effect of low-volume bowel preparations for colonoscopy preparation in China.

AIM: To evaluate the effect of sodium picosulfate/magnesium citrate (SPMC) and 3 L split-dose polyethylene glycol (PEG) with or without dimethicone on bowel preparation before colonoscopy. METHODS: In this multicenter, prospective, randomized, controlled study conducted from April 2021 to December 2021, consecutive adult patients scheduled for colonoscopy were prospectively randomized into four groups: SPMC, SPMC plus dimethicone, 3 L PEG, and 3 L PEG plus dimethicone. Primary endpoint was colon cleansing based on Boston Bowel Preparation Scale (BBPS). Secondary endpoints were bubble score, time to cecal intubation, adenoma detection rate (ADR), patient safety and compliance, and adverse events. RESULTS: We enrolled 223 and 291 patients in SPMC and 3 L PEG group, respectively. The proportion with acceptable bowel cleansing, total BBPS score and cecal intubation time were similar in all four subgroups (p > 0.05). Patient-reported acceptability and tolerability was significantly greater in SPMC than 3 L PEG group (p < 0.001); adverse events were significantly lower in SPMC than latter group (p < 0.001). ADR in both groups was greater than 30%. CONCLUSION: SPMC had significantly higher acceptability and tolerability than 3 L PEG, however, was similar in terms of bowel-cleansing effect and cecal intubation time and hence can be used before colonoscopy preparation.

Diagnostic value of contrast-enhanced ultrasound in judging the survival of graft after heteroautoplasty for secondary hyperparathyroidism.

BACKGROUND: Secondary hyperparathyroidism (SHPT) is one of the common complications of end-stage renal disease-uremia, and is mainly manifested as parathyroid hyperplasia and abnormal secretion of parathyroid hormone (PTH). OBJECTIVE: To investigate the value and advantages of contrast-enhanced ultrasound (CEUS) in evaluating the survival of autografts after parathyroidectomy + parathyroid autotransplantation. METHODS: In this study, 125 patients with renal failure due to polycystic kidney disease, chronic nephritis, diabetic nephropathy, lupus nephritis, and atherosclerotic nephropathy were enrolled as the participants and each of them had 4 secondary hyperactive parathyroid glands and underwent parathyroid autotransplantation. One parathyroid gland was taken from each patient and equally divided into 4 parts and placed in the subcutaneous fat of one forearm for transplantation. CEUS was performed 14 days after the transplantation to observe the micro blood supply of the graft and assess the survival and secretory function of the transplanted parathyroid. The grafts were divided into the partial survival group and the total survival group based on the enhancement characteristics. The survival of the grafts was determined by comparing the parathyroid hormone level in bilateral elbow cephalic veins 1 month after surgery. RESULTS: Among the 125 patients, 112 had linear or punctate enhancement of 2-4 parathyroid glands 14 days after surgery, and 13 patients had linear or punctate enhancement of 0-1 parathyroid gland. There were statistically significant differences in the perfusion pattern, enhancement uniformity, and parathyroid hormone levels in the cephalic veins at the elbow on both the graft and non-graft sides among all groups (P< 0.05). CONCLUSION: Compared to the detection of the difference in the parathyroid hormone level in the cephalic vein of bilateral elbows 1 month after surgery, CEUS can reflect the parathyroid survival after transplantation more quickly and accurately 2 weeks later, and provide a more rapid and agile non-invasive clinical diagnosis method.

[Retracted] Effects of Grb2­associated binding protein 2­specific siRNA on the migration and invasion of MG­63 osteosarcoma cells.

[This retracts the article DOI: 10.3892/ol.2017.7375.].

Effect of cadmium on histopathological injuries and ultra-structural changes of kidney of the turtle Mauremys reevesii.

This research investigated the effect of cadmium on the tissue and cell of kidney of the turtle Mauremys reevesii. Twenty turtles were injected with cadmium at 0, 7.5, 15, 30 mg/kg separately and five turtles were taken in each group at two weeks after exposure. Kidneys were immediately excised and macroscopic pathological changes were observed, then the kidneys were fixed in 4% paraformaldehyde for histopathological examination and fixed in 2.5% (v/v) glutaraldehyde for examination of ultra-structure. The tissues of kidney presented varying degrees of histopathological lesions in cadmium treated turtles by a dose-dependent manner under the light microscope. Under transmission electron microscope, renal tubules cells presented varying degrees of dose-dependent lesions. The results indicated that cadmium can cause cell damages to the kidney, in particular to the mitochondria. Mitochondria can be used as one biomarker in the monitoring of cadmium pollution and its quantitative risk assessments.

Hemoglobin Hydrolyzate Promotes Iron Absorption in the Small Intestine through Iron Binding Peptides.

Hemoglobin is an excellent source of iron supplements, and its hydrolyzate spontaneously binds iron during digestion and promotes iron absorption in vivo. However, the underlying mechanisms of what peptides bind and how they bind iron ions remain unclear. This study prepared the porcine hemoglobin hydrolyzate through enzymatic hydrolysis and acid treatment and investigated the mechanisms of hemoglobin hydrolyzate on iron absorption through the determination of iron levels in dietary intervention mice, iron binding site analyses, peptide digestion analyses, molecular simulation docking, and INT407 cell validation. The results showed that ingestion of the hemoglobin hydrolyzate diets increased iron levels in the blood of mice, accompanied by the upregulation of duodenal iron circulation-related genes such as ferritin, PCBP1, and HP. Carboxyl, imidazole groups, and aromatic amino acid residues were iron binding sites of hemoglobin hydrolyzate during digestion. VDEVGGEA and VDEVGGE were found to involve the spontaneous and efficient binding of hemoglobin hydrolyzate to iron ions in the intestinal cavity. In particular, the DEVGGE peptide was the typical sequence for hemoglobin hydrolytic peptides to exert iron binding activity.

Associations of Cadmium Exposure with Peripheral Blood Cell Subtype Counts and Indices in Cadmium-Poisoned Mice.

This research was designed to investigate the effects of cadmium on blood cell injury in cadmium-poisoned mice. Twenty mice were randomly divided into two groups: control group and model group. The control group was intraperitoneally injected with normal saline every day and the model group was intraperitoneally injected with 1.4 mg/kg cadmium solution every day. The experimental period was 28 days. The blood of the mice was collected for detection and hematological analysis. The results demonstrated that cadmium increased the number of white blood cells and the number of neutrophils in mice. Cadmium reduced the number of eosinophils, the number of basophils, the number of monocytes, the amount of lymphocytes, the number of red blood cells, the hemoglobin concentration, mean corpusular volume, mean corpusular hemoglobin, mean corpusular hemoglobin concentration, and the number of platelets in mice. In summary, cadmium caused some damage to white blood cells, red blood cells, and platelets in mice, but the direction of damage to different cells was inconsistent. The possible reason for this result is that cadmium damages the generation of blood cells, and the body takes corresponding defense measures.

The Combination of Gd-EOB-DTPA Enhanced T1 Mapping with Apparent Diffusion Coefficient could Improve the Diagnostic Efficacy of Hepatocellular Carcinoma Grading.

BACKGROUND: Accurately predicting the hepatocellular carcinoma (HCC) grade may facilitate the rational selection of treatment strategies. The diagnostic efficacy of the combination of Gadolinium ethoxybenzy diethylenetriamine pentaacetic (Gd-EOB-DTPA) enhancement T1 mapping and apparent diffusion coefficient (ADC) values in predicting HCC grade needs further validation. OBJECTIVES: This study aimed to assess the capacity of Gd-EOB-DTPA-enhanced T1 mapping and ADC values, both individually and in combination, to discriminate between different grades of HCC. MATERIALS AND METHODS: From July 2017 to February 2020, 96 patients (male, 83; mean age, 53.67 years; age range, 29-71 years) clinically diagnosed with HCC were included in the present study. All patients underwent Gd-EOB-DTPA-enhanced magnetic resonance imaging (MRI, including T1 mapping sequence) before surgery or biopsy. All the patients were categorized into 3 groups according to the pathological results (including 24 cases of well-differentiated HCCs, 59 cases of moderately differentiated HCCs, 13 cases of and poorly differentiated HCCs). The mean Gd-EOB-DTPA enhanced T1 values (ΔT1=[(T1pre-T1post)/T1pre]×100%) and ADC values between different grading groups of HCC were calculated and compared. The area under the characteristics curve (AUC), the diagnostic threshold, sensitivity, and specificity of ΔT1 and ADC for differential diagnosis were analyzed. RESULTS: Mean ΔT1 was 58% for well-differentiated HCCs, 50% for moderately-differentiated HCCs, and 43% for poorly-differentiated HCCs. ΔT1 showed statistical differences between the groups (P<0.001). The mean ADC values of the 3 groups were 1.11×10-3 mm2/s, 0.91×10-3 mm2/s, and 0.80×10-3mm2/s, respectively. ADC showed statistical differences between the groups (P<0.001). In discriminating well- differentiated group from the moderately differentiated group, the AUC of ΔT1 was 0.751 (95% CI: 0.642, 0.859), the AUC of ADC was 0.782 (95% CI: 0.671, 0.894), the AUC of combined model was 0.811 (95% CI: 0.709, 0.914). In discriminating the poorly differentiated group from the moderately differentiated group, the AUC of ΔT1 was 0.768 (95% CI: 0.634, 0.902), the AUC of ADC was 0.754 (95% CI: 0.603, 0.904), and the AUC of the combined model was 0.841 (95% CI: 0.729, 0.953). CONCLUSION: Gd-EOB-DTPA enhanced T1 mapping, and ADC values have complementary effects on the sensitivity and specificity for identifying different HCC grades. A combined model of Gd-EOB-DTPA-enhanced MRI T1 mapping and ADC values could improve diagnostic performance for predicting HCC grades.

A Primer for Utilizing Deep Learning and Abdominal MRI Imaging Features to Monitor Autosomal Dominant Polycystic Kidney Disease Progression.

Abdominal imaging of autosomal dominant polycystic kidney disease (ADPKD) has historically focused on detecting complications such as cyst rupture, cyst infection, obstructing renal calculi, and pyelonephritis; discriminating complex cysts from renal cell carcinoma; and identifying sources of abdominal pain. Many imaging features of ADPKD are incompletely evaluated or not deemed to be clinically significant, and because of this, treatment options are limited. However, total kidney volume (TKV) measurement has become important for assessing the risk of disease progression (i.e., Mayo Imaging Classification) and predicting tolvaptan treatment's efficacy. Deep learning for segmenting the kidneys has improved these measurements' speed, accuracy, and reproducibility. Deep learning models can also segment other organs and tissues, extracting additional biomarkers to characterize the extent to which extrarenal manifestations complicate ADPKD. In this concept paper, we demonstrate how deep learning may be applied to measure the TKV and how it can be extended to measure additional features of this disease.

A new clinical model for predicting lymph node metastasis in T1 colorectal cancer.

PURPOSE: Lymph node metastasis (LNM) is a crucial factor that determines the prognosis of T1 colorectal cancer (CRC) patients. We aimed to develop a practical prediction model for LNM in T1 CRC. METHODS: We conducted a retrospective analysis of data from 825 patients with T1 CRC who underwent radical resection at a single center in China. All enrolled patients were randomly divided into a training set and a validation set at a ratio of 7:3 using R software. Risk factors for LNM were identified through multivariate logistic regression analyses. Subsequently, a prediction model was developed using the selected variables. RESULTS: The lymph node metastasis (LNM) rate was 10.1% in the training cohort and 9.3% in the validation cohort. In the training set, risk factors for LNM in T1 CRC were identified, including depressed endoscopic gross appearance, sex, submucosal invasion combined with tumor grade (DSI-TG), lymphovascular invasion (LVI), and tumor budding. LVI emerged as the most potent predictor for LNM. The prediction model based on these factors exhibited good discrimination ability in the validation sets (AUC: 79.3%). Compared to current guidelines, the model could potentially reduce over-surgery by 48.9%. Interestingly, we observed that sex had a differential impact on LNM between early-onset and late-onset CRC patients. CONCLUSIONS: We developed a clinical prediction model for LNM in T1 CRC using five factors that are easily accessible in clinical practice. The model has better predictive performance and practicality than the current guidelines and can assist clinicians in making treatment decisions for T1 CRC patients.

The mechanism of USP43 in the development of tumor: a literature review.

Ubiquitination of the proteins is crucial for governing protein degradation and regulating fundamental cellular processes. Deubiquitinases (DUBs) have emerged as significant regulators of multiple pathways associated with cancer and other diseases, owing to their capacity to remove ubiquitin from target substrates and modulate signaling. Consequently, they represent potential therapeutic targets for cancer and other life-threatening conditions. USP43 belongs to the DUBs family involved in cancer development and progression. This review aims to provide a comprehensive overview of the existing scientific evidence implicating USP43 in cancer development. Additionally, it will investigate potential small-molecule inhibitors that target DUBs that may have the capability to function as anti-cancer medicines.

Investigation of the correlation between platelet antibodies and peripheral blood cytopenia in patients with hepatocellular carcinoma.

The primary triggers that stimulate the body to generate platelet antibodies via immune mechanisms encompass events such as pregnancy, transplantation, and blood transfusion. Interestingly, our findings revealed that a subset of male patients with hepatocellular carcinoma (HCC), despite having no history of transplantation or blood transfusion, has shown positive results in platelet antibody screenings. This hints at the possibility that certain factors, potentially related to the tumor itself or its treatment, may affect antibody production. To delve the causes we initiated this study. We employed a case-control study approach to analyze potential influential factors leading to the positive results via univariate and multivariate regression analysis. We utilized Kendall's tau-b correlation to examine the relationship between the strength of platelet antibodies and peripheral blood cytopenia. Antitumor medication emerged as an independent risk factor for positive results in HCC patients, and the strength of platelet antibodies positively correlated with the severity of anemia and thrombocytopenia. Without history of blood transfusion, transplantation, pregnancy, those HCC patients underwent recent tumor medication therapy are experiencing peripheral erythrocytopenia or thrombocytopenia, for them platelet antibody screenings holds potential clinical value for prevention and treatment of complications like drug-immune-related anemia and/or bleeding.

PLK3 is linked with higher tumor stage and unfavorable prognosis in patients with colorectal cancer.

Objective: This study intended to explore the relationship of PLK3 with prognosis in patients with colorectal cancer (CRC). Methods: PLK3 positivity was detected by immunohistochemistry in 160 patients with CRC receiving surgical resection. Results: The median tumor PLK3-positive rate was 26.5%. Tumor PLK3-positive rate was related to increased lymph node stage (p = 0.002) and tumor-node-metastasis stage (p < 0.001) of CRC. Tumor PLK3-positive rate ≥30% was related to shortened disease-free survival (p = 0.009) and overall survival (p = 0.003); tumor PLK3-positive rate ≥50% showed a stronger correlation with them (both p = 0.001), which was validated by multivariate Cox regression analyses (both p < 0.05). Conclusion: Tumor PLK3-positive rate ≥50% relates to increased tumor stage and unfavorable survival in patients with CRC.

[Box: see text].

Diallyl disulfide antagonizes DJ-1 mediated proliferation, epithelial-mesenchymal transition, and chemoresistance in gastric cancer cells.

Diallyl disulfide (DADS), an organic component of allicin abstracted from garlic, possesses multi-target antitumor activity. DJ-1 performs a vital function in promoting AKT aberrant activation via down-regulating phosphatase and tensin homologue (PTEN) in tumors. It is unknown the involvement of DJ-1 in epithelial-mesenchymal transition (EMT) of gastric cancer (GC) cells. The purpose of this study is to investigate whether diallyl disulfide (DADS) intervenes in the role of DJ-1 in GC. Based on the identification that the correlation between high DJ-1 and low PTEN expression in GC was implicated in clinical progression, we illuminated that down-regulation of DJ-1 by DADS aided in an increase in PTEN expression and a decrease in phosphorylated AKT levels, which was in line with the results manifested in the DJ-1 knockdown and overexpressed cells, concurrently inhibiting proliferation, EMT, migration, and invasion. Furthermore, the antagonistic effects of DADS on DJ-1 were observed in in vivo experiments. Additionally, DADS mitigated the DJ-1-associated drug resistance. The current study revealed that DJ-1 is one of potential targets for DADS, which hopefully provides a promising strategy for prevention and adjuvant chemotherapy of GC.

Integrated proteogenomic and metabolomic characterization of papillary thyroid cancer with different recurrence risks.

Although papillary thyroid cancer (PTC) has a good prognosis, its recurrence rate is high and remains a core concern in the clinic. Molecular factors contributing to different recurrence risks (RRs) remain poorly defined. Here, we perform an integrative proteogenomic and metabolomic characterization of 102 Chinese PTC patients with different RRs. Genomic profiling reveals that mutations in MUC16 and TERT promoter as well as multiple gene fusions like NCOA4-RET are enriched by the high RR. Integrative multi-omics analyses further describe the multi-dimensional characteristics of PTC, especially in metabolism pathways, and delineate dominated molecular patterns of different RRs. Moreover, the PTC patients are clustered into four subtypes (CS1: low RR and BRAF-like; CS2: high RR and metabolism type, worst prognosis; CS3: high RR and immune type, better prognosis; CS4: high RR and BRAF-like) based on the omics data. Notably, the subtypes display significant differences considering BRAF and TERT promoter mutations, metabolism and immune pathway profiles, epithelial cell compositions, and various clinical factors (especially RRs and prognosis) as well as druggable targets. This study can provide insights into the complex molecular characteristics of PTC recurrences and help promote early diagnosis and precision treatment of recurrent PTC.