A novel model combining genes associated with disulfidptosis and glycolysis to predict breast cancer prognosis, molecular subtypes, and treatment response.

Breast cancer (BC) is a heterogeneous malignancy with a dismal prognosis. Disulfidptosis is a novel type of regulated cell death that happens in the presence of glucose deficiency and is linked to the metabolic process of glycolysis. However, the mechanism of action of disulfidptosis and glycolysis-related genes (DGRG) in BC, as well as their prognostic value in BC patients, remain unknown. After identifying the differentially expressed DGRG in normal and BC tissues, a number of machine learning algorithms were utilized to select essential prognostic genes to develop a model, including SLC7A11, CACNA1H, SDC1, CHST1, and TFF3. The expression characteristics of these genes were then examined using single-cell RNA sequencing, and BC was classified into three clusters using "ConsensusClusterPlus" based on these genes. The DGRG model's median risk score can categorize BC patients into high-risk and low-risk groups. Furthermore, we investigated variations in clinical landscape, immunoinvasion analysis, tumor immune dysfunction and rejection (TIDE), and medication sensitivity in patients in the DGRG model's high- and low-risk groups. Patients in the low-risk group performed better on immunological and chemotherapeutic therapies and had lower TIDE scores. In conclusion, the DGRG model we developed has significant clinical application potential because it can accurately predict the prognosis of BC, TME, and pharmacological treatment responses.

MBD-Net: Multi-Branch Dilated Convolutional Network With Cyst Discriminator for Renal Multi-Structure Segmentation.

In surgery-based renal cancer treatment, one of the most essential tasks is the three-dimensional (3D) kidney parsing on computed tomography angiography (CTA) images. In this paper, we propose an end-to-end convolutional neural network-based framework to segment multiple renal structures, including kidneys, kidney tumors, arteries, and veins from arterial-phase CT images. Our method consists of two collaborative modules: First, we propose an encoding-decoding network, named Multi-Branch Dilated Convolutional Network (MBD-Net), consisting of residual, hybrid dilated convolutional, and reduced-dimensional convolutional structures, which improves the feature extraction ability with relatively fewer network parameters. Given that renal tumors and cysts have confusing geometric structures, we also design the Cyst Discriminator to effectively distinguish tumors from cysts without labeling information via gray-scale curves and radiographic features. We have quantitatively evaluated our approach on a publicly available dataset from MICCAI 2022 Kidney Parsing for Renal Cancer Treatment Challenge (KiPA2022), with mean Dice similarity coefficient (DSC) as 96.18%, 90.99%, 88.66% and 80.35% for the kidneys, kidney tumors, arteries, and veins respectively, winning the stable and top performance in the challenge.Clinical relevance-The proposed CNN-Based framework can automatically segment 3D kidneys, renal tumors, arteries, and veins for kidney parsing techniques, benefiting surgery-based renal cancer treatment.

A ubiquitin-proteasome system-related signature to predict prognosis, immune infiltration, and therapy efficacy for breast cancer.

The ubiquitin-proteasome system (UPS) is an essential regulatory system for maintaining homeostasis, and its dysfunction may cause various diseases. The activity of proteasome and ubiquitin-conjugating enzymes has been found to be greatly increased in breast cancer (BC), indicating that the heterogeneity of UPS may be related to the progression of BC. Gene data was obtained from The Cancer Genome Atlas and Gene Expression Omnibus databases and performed in multiple algorithms to construct a UPS-related signature for BC. Patients in the UPS low-risk group had greater overall and recurrence-free survival probability than those in the UPS high-risk group. This signature was closely associated with functional enrichment. Some high metabolism-related pathways were more active in the UPS high-risk group. The UPS low-risk group had more abundant anti-tumor immune cells, while in the UPS high-risk group, immunosuppressive cells were dominant. More importantly, we found that the UPS low-risk group was more sensitive to immunotherapy, while the UPS high-risk group responded better to radiotherapy. Drug sensitivity analysis identified more effective chemotherapy drugs in different UPS-related risk groups. This UPS-related signature may serve as a novel biomarker and independent prognostic factor for BC. It can effectively predict prognosis, immune infiltration, and therapy efficacy, providing new strategies for individualized treatment.

Diagnostic value of contrast-enhanced ultrasound for sentinel lymph node metastasis in breast cancer: an updated meta-analysis.

PURPOSE: The status of sentinel lymph nodes (SLN) is an important factor in determining the stage of breast cancer (BC) and the surgical procedure, and also a biomarker of the BC prognosis. This meta-analysis was performed to investigate the diagnostic value of contrast-enhanced ultrasound (CEUS) for SLN metastasis. METHODS: A systematic search was conducted for relevant articles published in the PubMed, Embase, Web of Science, OVID databases, and Cochrane Library from inception to March 2023. We calculated the sensitivity, specificity, positive and negative likelihood ratio (PLR; NLR), diagnostic odds ratio (DOR), and summary receiver operator characteristic (SROC) curve to evaluate the diagnostic efficacy of CEUS in SLN metastasis. Subgroup analysis was also performed to investigate potential sources of heterogeneity. RESULTS: A total of 12 studies with 1525 patients were included in this meta-analysis. The overall pooled sensitivity and specificity of CEUS in the diagnosis of SLN metastasis were 0.91 (95% CI: 0.84-0.95) and 0.86 (95% CI: 0.78-0.92). The PLR, NLR, and DOR were 6.51 (95% CI: 4.09-10.36), 0.11 (95% CI: 0.07-0.18), and 59.43 (95% CI: 33.27-106.17), respectively, and the area under the SROC curve was determined to be 0.95 (95%CI: 0.92-0.96), all showing excellent diagnostic value. In the subgroup analysis, percutaneous CEUS was more sensitive than intravenous CEUS in the diagnosis of SLN metastases (0.92 versus 0.82, p < 0.05). CONCLUSION: CEUS, especially percutaneous CEUS, is a reliable imaging technique for diagnosing SLN metastasis and providing important information in the stage management of breast cancer.

Prognosis stratification and response to treatment in breast cancer based on one-carbon metabolism-related signature.

Introduction: Breast cancer (BC) is the most common malignant tumor in the female population. Despite staging and treatment consensus guidelines, significant heterogeneity exists in BC patients' prognosis and treatment efficacy. Alterations in one-carbon (1C) metabolism are critical for tumor growth, but the value of the role of 1C metabolism in BC has not been fully investigated. Methods: To investigate the prognostic value of 1C metabolism-related genes in BC, 72 1C metabolism-related genes from GSE20685 dataset were used to construct a risk-score model via univariate Cox regression analysis and the least absolute shrinkage and selection operator (LASSO) regression algorithm, which was validated on three external datasets. Based on the risk score, all BC patients were categorized into high-risk and low-risk groups. The predictive ability of the model in the four datasets was verified by plotting Kaplan-Meier curve and receiver operating characteristic (ROC) curve. The candidate genes were then analyzed in relation to gene mutations, gene enrichment pathways, immune infiltration, immunotherapy, and drug sensitivity. Results: We identified a 7-gene 1C metabolism-related signature for prognosis and structured a prognostic model. ROC analysis demonstrated that the model accurately predicted the 2-, 3-, and 5-year overall survival rate of BC patients in the four cohorts. Kaplan-Meier analysis revealed that survival time of high-risk patients was markedly shorter than that of low-risk patients (p < 0.05). Meanwhile, high-risk patients had a higher tumor mutational burden (TMB), enrichment of tumor-associated pathways such as the IL-17 signaling pathway, lower levels of T follicular helper (Tfh) and B cells naive infiltration, and poorer response to immunotherapy. Furthermore, a strong correlation was found between MAT2B and CHKB and immune checkpoints. Discussion: These findings offer new insights into the effect of 1C metabolism in the onset, progression, and therapy of BC and can be used to assess BC patients' prognosis, study immune infiltration, and develop potentially more effective clinical treatment options.

Diagnosis accuracy of Raman spectroscopy in the diagnosis of breast cancer: a meta-analysis.

To investigate the diagnostic efficiency of Raman spectroscopy for the diagnosis of breast cancer, we searched PubMed, Web of Science, Cochrane Library, and Embase for articles published from the database establishment to May 20, 2022. Pooled sensitivity, specificity, diagnostic odds ratio, and area under the receiver pooled operating characteristic curve were derived for the included studies as outcome measures. The methodological quality was assessed according to the questionnaires and criteria suggested by the Diagnostic Accuracy Research Quality Assessment-2 tool. Sixteen studies were included in this meta-analysis. The pooled sensitivity and specificity of Raman spectroscopy for breast cancer diagnosis were 0.97 (95% CI, [0.92-0.99]) and 0.96 (95% CI, [0.91-0.98]). The diagnostic odds ratio was 720.89 (95% CI, [135.73-3828.88]) and the area under the curve of summary receiver operating characteristic curves was 0.99 (95% CI, [0.98-1]). Subgroup analysis revealed that all subgroup types in our analysis, including different races, sample types, diagnostic algorithms, number of spectra, instrument types, and laser wavelengths, turned out to have a sensitivity and specificity greater than 0.9. Significant heterogeneity was found between studies. Deeks' funnel plot demonstrated that publication bias was acceptable. This meta-analysis suggests that Raman spectroscopy may be an effective and accurate tool to differentiate breast cancer from normal breast tissue, which will help us diagnose and treat breast cancer.

Safety and efficacy of ultrasound-guided thermal ablation in treating T1aN0M0 and T1bN0M0 papillary thyroid carcinoma: A meta-analysis.

Background: Papillary thyroid cancer (PTC) is the most common thyroid tumor, and early diagnosis and treatment can effectively improve prognosis. Many controversies surround the treatment method of T1N0M0 PTC. Recently, thermal ablation (TA) has shown some benefits in the treatment of PTC patients, but the safety and efficacy of its treatment remain controversial. This article performs a meta-analysis of TA in patients with T1aN0M0 and T1bN0M0 PTC. Methods: The PubMed, Embase, Web of Science, and Cochrane Library databases were systematically searched for retrospective or prospective studies of TA for treating patients with T1N0M0 PTC from the database establishment to May 1, 2022. Data on volume reduction rate (VRR), disease progress, and complication rate were collected. In addition, a meta-analysis was performed using the Stata 12.0 and Review Manager 5.3. Results: A total of 9 eligible studies were included. Our study demonstrated the effectiveness of VRR and disease progress. The VRR was reduced after 3 months (-75.90%; 95% CI [-118.46-33.34%]), 6 months (34.33%; 95% CI [15.01-53.65%]), 12 months (78.69%; 95% CI [71.69-85.68%]), and 24 months (89.97%; 95% CI [84.00-95.94%]). The disease progress was 1.9% (95% CI [1.1-3.0]). Safety is justified by the complication rate, which was 6.5% (95% CI [3.5-10.2]). Pain and hoarseness were the most common complications, and no life-threatening complications were reported. Egger's test demonstrated that publication bias was acceptable. Conclusions: TA is an effective and safe method for managing T1aN0M0 and T1bN0M0 papillary thyroid nodules.

A circadian rhythm-related gene signature for prognosis, invasion and immune microenvironment of breast cancer.

Background: Circadian dysregulation is linked to the onset and progression of cancer, but current knowledge of the role of circadian rhythm-related genes (CRRGs) in breast cancer (BC) is limited and incomplete. The purpose of this study was to investigate the potential role and immune-related prognostic significance of CRRGs in BC. Methods: The Cancer Genome Atlas breast cancer (TCGA-BRCA) genetic data were combined with 1369 CRRGs to create a model of BC prognosis-related CRRGs. To validate the model's predictive power in TCGA and other external datasets, the Kaplan-Meier survival curve and receptor operation characteristic curve were plotted. The relationship between CRRGs model and gene enrichment pathways, immune cell infiltration, and differences in patient response to immune checkpoint inhibitors (ICIs) therapy was then discussed. Results: A CRRG-based eighteen-gene model was developed that accurately predicted the survival time of BC patients. Based on this model, BC patients can be classified as high or low risk. The high-risk group has negative immune cell infiltration (such as macrophages M0 and M2) and a poor therapeutic response to ICIs due to lower immune checkpoint gene expression. Furthermore, TCF7 and IFNG were found to be strongly associated with immune checkpoints in CRRGs model. Conclusion: The 18 CRRGs may be useful in assessing the prognosis of BC patients, studying immune infiltration, and developing more effective immunotherapy strategies.

Cytosolic BolA Plays a Repressive Role in the Tolerance against Excess Iron and MV-Induced Oxidative Stress in Plants.

The BolA-like protein is present in all eukaryotes, and it is able to form complex with monothiol glutaredoxin of the same subcellular compartments, suggesting that the BolA-like protein has essential function in eukaryotes, and that the function is associated with its partner glutaredoxin. Some studies have indicated a role for BolA proteins in Fe-S cluster synthesis or in redox homeostasis. However, the physiological function of BolA proteins remains to be elucidated. Here, we report the characterization of an insertion mutant of BolA3 in Arabidopsis. Among the four AtBolA proteins found in Arabidopsis, the AtBolA3 was the only BolA located in the cytosol of plant cells. It was highly expressed in roots. AtBolA3 was able to interact with the cytosolic monothiol glutaredoxin, AtGRXS17. The bola3 mutant did not show any notable phenotype under normal growth condition, but rather grew better than wild type under some stresses. The bola3 mutant was more tolerant to excess iron and the MV-induced oxidative stress than wild type. It displayed no necrosis in leaves, developed longer roots, accumulated more iron and higher Fe-S protein activities in roots. In addition, the mutant possessed a more potent antioxidant defense to scavenge ROS species. Taken together, our data indicated that the cytosolic AtBolA3 has a suppressive role in the tolerance to excess iron and the MV-induced oxidative stress in plants. AtBolA3 seems to be a repressor under some stress conditions.

Soybean Fe-S cluster biosynthesis regulated by external iron or phosphate fluctuation.

KEY MESSAGE: Iron and phosphorus are essential for soybean nodulation. Our results suggested that the deficiency of Fe or P impairs nodulation by affecting the assembly of functional iron-sulfur cluster via different mechanisms. Iron (Fe) and phosphorus (P) are important mineral nutrients for soybean and are indispensable for nodulation. However, it remains elusive how the pathways of Fe metabolism respond to the fluctuation of external Fe or P. Iron is required for the iron-sulfur (Fe-S) cluster assembly in higher plant. Here, we investigated the expression pattern of Fe-S cluster biosynthesis genes in the nodulated soybean. Soybean genome encodes 42 putative Fe-S cluster biosynthesis genes, which were expressed differently in shoots and roots, suggesting of physiological relevance. Nodules initiated from roots of soybean after rhizobia inoculation. In comparison with that in shoots, iron concentration was three times higher in nodules. The Fe-S cluster biosynthesis genes were activated and several Fe-S protein activities were increased in nodules, indicating that a more effective Fe-S cluster biosynthesis is accompanied by nodulation. Fe-S cluster biosynthesis genes were massively repressed and some Fe-S protein activities were decreased in nodules by Fe deficiency, leading to tiny nodules. Notably, P deficiency induced a similar Fe-deficiency response in nodules, i.e, certain Fe-S enzyme activity loss and tiny nodules. However, distinct from Fe-deficient nodules, higher iron concentration was accumulated and the Fe-S cluster biosynthesis genes were not suppressed in the P-deficiency-treated nodules. Taken together, our results showed that both Fe deficiency and P deficiency impair nodulation, but they affect the assembly of Fe-S cluster maybe via different mechanisms. The data also suggested that Fe-S cluster biosynthesis likely links Fe metabolism and P metabolism in root and nodule cells of soybean.

Genes for iron-sulphur cluster assembly are targets of abiotic stress in rice, Oryza sativa.

Iron-sulphur (Fe-S) cluster assembly occurs in chloroplasts, mitochondria and cytosol, involving dozens of genes in higher plants. In this study, we have identified 41 putative Fe-S cluster assembly genes in rice (Oryza sativa) genome, and the expression of all genes was verified. To investigate the role of Fe-S cluster assembly as a metabolic pathway, we applied abiotic stresses to rice seedlings and analysed Fe-S cluster assembly gene expression by qRT-PCR. Our data showed that genes for Fe-S cluster assembly in chloroplasts of leaves are particularly sensitive to heavy metal treatments, and that Fe-S cluster assembly genes in roots were up-regulated in response to iron toxicity, oxidative stress and some heavy metal assault. The effect of each stress treatment on the Fe-S cluster assembly machinery demonstrated an unexpected tissue or organelle specificity, suggesting that the physiological relevance of the Fe-S cluster assembly is more complex than thought. Furthermore, our results may reveal potential candidate genes for molecular breeding of rice.