An unsupervised learning model based on CT radiomics features accurately predicts axillary lymph node metastasis in breast cancer patients-diagnostic study.

BACKGROUND: The accuracy of traditional clinical methods for assessing the metastatic status of axillary lymph nodes is unsatisfactory. In this study, we propose the use of radiomic technology and three-dimensional (3D) visualization technology to develop an unsupervised learning model for predicting axillary lymph node metastasis in patients with breast cancer, aiming to provide a new method for clinical axillary lymph node assessment in patients with this disease. METHODS: In this study, we retrospectively analyzed the data of 350 patients with invasive breast cancer who underwent lung-enhanced CT and axillary lymph node dissection (ALND) surgery at the Department of Breast Surgery of the XXX Hospital of XXX University. We used 3D visualization technology to create a 3D atlas of axillary lymph nodes and identified the region of interest (ROI) for the lymph nodes. Radiomic features were subsequently extracted and selected, and a prediction model for axillary lymph nodes was constructed using the K-means unsupervised algorithm. To validate the model, we prospectively collected data from 128 breast cancer patients who were clinically evaluated as negative at our center. RESULTS: Using 3D visualization technology, we extracted and selected a total of 36 CT radiomics features. The unsupervised learning model categorized 1737 unlabeled lymph nodes into two groups, and the analysis of the radiomic features between these groups indicated potential differences in lymph node status. Further validation with 1397 labeled lymph nodes demonstrated that the model had good predictive ability for axillary lymph node status, with an area under the curve (AUC) of 0.847 (0.825-0.869). Additionally, the model's excellent predictive performance was confirmed in the 128 axillary clinical assessment negative cohort (cN0) and the 350 clinical assessment positive (cN+) cohort, for which the correct classification rates (CCR) were 86.72% and 87.43%, respectively, which were significantly greater than those of clinical assessment methods. CONCLUSIONS: We created an unsupervised learning model that accurately predicts the status of axillary lymph nodes. This approach offers a novel solution for the precise assessment of axillary lymph nodes in patients with breast cancer.

Comparison of neoadjuvant chemotherapy response and prognosis between HR-low/HER2-negative BC and TNBC: an exploratory real-world multicentre cohort study.

Objective: Hormone receptor (HR)-low/HER2-negative breast cancers (BCs) are more likely to be basal-like BCs, with similar molecular features and gene expression profiles to HR-negative (estrogen receptor <1% or negative and progesterone receptor <1% or negative) BCs. Recently, with the clinical application of adjuvant intensive therapy for triple-negative breast cancer (TNBC), the prognosis of TNBC patients without pathological complete response (pCR) has significantly improved. Therefore, it is necessary to reanalyse the prognostic characteristics of clinically high-risk HR-low/HER2-negative BC. Methods: According to the inclusion and exclusion standards, 288 patients with HR-low/HER2-negative BC and TNBC who received NAC and were followed up between 2015 and 2022 at three breast centres in Hunan Province, China, were enrolled. Inverse probability of treatment weighting (IPTW) was utilized to mitigate imbalances in baseline characteristics between the HR-low/HER2-negative BC group and TNBC group regarding event-free survival (EFS) and overall survival (OS). The primary clinical endpoints were pCR and EFS, while the secondary endpoints included OS, objective response rate (ORR), and clinical benefit rate (CBR). Results: The pCR rate (27.1% vs. 28.0%, P = 1.000), ORR rate (76.9% vs. 78.3%, P = 0.827) and CBR rate (89.7% vs. 96.5%, P = 0.113) after NAC were similar between the HR-low/HER2-negative BC and the TNBC group. EFS in patients with non-pCR from the 2 groups was significantly inferior in comparison to patients with pCR (P = 0.001), and the 3-year EFS was 94.74% (95% CI = 85.21% to 100.00%) and 57.39% (95% CI =43.81% to 75.19%) in patients with pCR and non-pCR from the HR-low/HER2-negative BC group, respectively, and 89.70% (95% CI = 82.20% to 97.90%) and 69.73% (95% CI = 62.51% to 77.77%) in the TNBC patients with pCR and non-pCR, respectively. Conclusions: In the real world, the therapeutic effects of NAC for HR-low/HER2-negative BCs and TNBCs were similar. EFS of patients with non-pCR in the HR-low/HER2-negative BC group was inferior to that of the TNBC group with non-pCR, suggesting that it is necessary to explore new adjuvant intensive therapy strategies for these patients.

Identification of exosome-related gene signature as a promising diagnostic and therapeutic tool for breast cancer.

Background: Exosomes are promising tools for the development of new diagnostic and therapeutic approaches. Exosomes possess the ability to activate signaling pathways that contribute to the remodeling of the tumor microenvironment, angiogenesis, and the regulation of immune responses. We aimed to develop a prognostic score based on exosomes derived from breast cancer. Materials and methods: Training was conducted on the TCGA-BRCA dataset, while validation was conducted on GSE20685, GSE5764, GSE7904, and GSE29431. A total of 121 genes related to exosomes were retrieved from the ExoBCD database. The Cox proportional hazards model is used to develop risk score model. The GSVA package was utilized to analyze single-sample gene sets and identify exosome signatures, while the WGCNA package was utilized to identify gene modules associated with clinical outcomes. The clusterProfiler and GSVA R packages facilitated gene set enrichment and variation analyses. Furthermore, CIBERSORT quantified immune infiltration, and a correlation between gene expression and drug sensitivity was assessed using the TIDE algorithm. Results: An exosome-related prognostic score was established using the following selected genes: ABCC9, PIGR, CXCL13, DOK7, CD24, and IVL. Various immune cells that promote cancer immune evasion were associated with a high-risk prognostic score, which was an independent predictor of outcome. High-risk and low-risk groups exhibited significantly different infiltration abundances (p < 0.05). By conducting a sensitivity comparison, we found that patients with high-risk scores exhibited more favorable responses to immunotherapy than those with low-risk scores. Conclusion: The exosome-related gene signature exhibits outstanding performance in predicting the prognosis and cancer status of patients with breast cancer and guiding immunotherapy.

An engineered Cas12i nuclease that is an efficient genome editing tool in animals and plants.

The type V-I CRISPR-Cas system is becoming increasingly more attractive for genome editing. However, natural nucleases of this system often exhibit low efficiency, limiting their application. Here, we used structure-guided rational design and protein engineering to optimize an uncharacterized Cas12i nuclease, Cas12i3. As a result, we developed Cas-SF01, a Cas12i3 variant that exhibits significantly improved gene editing activity in mammalian cells. Cas-SF01 shows comparable or superior editing performance compared to SpCas9 and other Cas12 nucleases. Compared to natural Cas12i3, Cas-SF01 has an expanded PAM range and effectively recognizes NTTN and noncanonical NATN and TTVN PAMs. In addition, we identified an amino acid substitution, D876R, that markedly reduced the off-target effect while maintaining high on-target activity, leading to the development of Cas-SF01HiFi (high-fidelity Cas-SF01). Finally, we show that Cas-SF01 has high gene editing activities in mice and plants. Our results suggest that Cas-SF01 can serve as a robust gene editing platform with high efficiency and specificity for genome editing applications in various organisms.

Immune characteristics and clinical significance of peripheral blood lymphocytes in breast cancer.

BACKGROUND: In the context of breast cancer (BC), the correlation between lymphocytes and clinical outcomes, along with treatment response, has garnered attention. Despite this, few investigations have delved into the interplay among distinct peripheral blood lymphocyte (PBL) types, immune attributes, and their clinical implications within the BC landscape. METHODS: The primary objective of this study was to scrutinize the baseline status of PBL subsets in patients with primary BC, track their dynamic changes throughout treatment, and ascertain their interrelation with prognosis. Flow cytometry was employed to analyse PBLs from a cohort of 74 BC patients. RESULTS: Our analysis revealed that baseline levels of Treg and PD-L1 + T cells were lower in BC patients compared to the reference values. Notably, a disparity in baseline PD-L1 + T cell levels surfaced between patients who underwent adjuvant therapy and those subjected to neoadjuvant therapy (NAT). Furthermore, a meticulous evaluation of PBL subsets before and after treatment underscored discernible alterations in 324 + T cells and CD19 + CD32 + B cells over the course of therapy. Strikingly, heightened CD4 + T cell levels at baseline were linked to enhanced event-free survival (EFS) (p = 0.02) and a robust response to chemotherapy. CONCLUSIONS: These results indicate that PBLs may serve as a significant marker to assess the immune status of BC patients, and therapy has the potential to modify patient immune profiles. In addition, peripheral blood CD4 + T cell levels may serve as promising biomarkers for diagnosis and prognosis in future studies of BC.

Comparative effectiveness of nipple-sparing mastectomy and breast-conserving surgery on long-term prognosis in breast cancer.

Background: The frequency of nipple-sparing mastectomy (NSM) surgery is presently increasing. Nonetheless, there is a paucity of long-term prognosis data on NSM. This study compared the long-standing prognosis of NSM in relation to breast-conserving surgery (BCS). Methods: Population-level data for 438,588 female breast cancer patients treated with NSM or BCS and postoperative radiation from 2000 to 2018 were identified in the Surveillance, Epidemiology, and End Results (SEER) database; 321 patients from the Second Xiangya Hospital of Central South University were also included. Propensity score matching (PSM) was performed to reduce the influence of selection bias and confounding variables to make valid comparisons. The Kaplan-Meier analysis, log-rank test, and Cox regression were applied to analyze the data. Results: There were no significant differences in long-term survival rates between patients who underwent NSM and those who underwent BCS+radiotherapy (BCS+RT), as indicated by the lack of significant differences in overall survival (OS) (p = 0.566) and breast cancer-specific survival (BCSS) (p = 0.431). Cox regression indicated that NSM and BCS+RT had comparable prognostic values (p = 0.286) after adjusting for other clinicopathological characteristics. For OS and BCSS, subgroup analysis showed that the majority of patients achieved an analogous prognosis whether they underwent NSM or BCS. The groups had comparable recurrence-free survival (RFS), with no significant difference found (p = 0.873). Conclusions: This study offers valuable insights into the long-term safety and comparative effectiveness of NSM and BCS in the treatment of breast cancer. These findings can assist clinicians in making informed decisions on a case-by-case basis.

Multi-omics analysis reveals the involvement of origin recognition complex subunit 6 in tumor immune regulation and malignant progression.

Background: Origin recognition complex 6 (ORC6) is one of the six highly conserved subunit proteins required for DNA replication and is essential for maintaining genome stability during cell division. Recent research shows that ORC6 regulates the advancement of multiple cancers; however, it remains unclear what regulatory impact it has on the tumor immune microenvironment. Methods: Unpaired Wilcoxon rank sum and signed rank tests were used to analyze the differences in the expression of ORC6 in normal tissues and corresponding tumor tissues. Multiple online databases have evaluated the genetic alterations, protein expression and localization, and clinical relevance of ORC6. To evaluate the potential prognostic impact and diagnostic significance of ORC6 expression, we carried out log-rank, univariate Cox regression, and receiver operating characteristic curve analysis. The ICGC-LIRI-JP cohort, CGGA-301 cohort, CGGA-325 cohort, CGGA-693 cohort, and GSE13041 cohort were used for external validation of the study findings. The associations between ORC6 expression and immune cell infiltration, immune checkpoint expression, and immunotherapy cohorts was further analyzed. To explore the functional and signaling pathways related to ORC6 expression, gene set enrichment analysis was performed. To clarify the expression and function of ORC6 in hepatocellular carcinoma (LIHC) and glioma, we conducted in vitro experiments. Results: Expression of ORC6 is upregulated in the majority of cancer types and is associated with poor patient prognosis, notably in cases of LIHC and gliomas. In addition, ORC6 may be involved in multiple signaling pathways related to cancer progression and immune regulation. High expression of ORC6 correlates with an immunosuppressive state in the tumor microenvironment. The results of further immunotherapy cohort analysis suggested that patients in the ORC6 high-expression group benefited from immunotherapy. Inhibiting ORC6 expression suppressed the proliferative and migratory abilities of LIHC and glioma cells. Conclusion: High expression of ORC6 may be used as a biomarker to predict the poor prognosis of most tumor patients. The high expression of ORC6 may be involved in the regulation of the tumor immunosuppressive environment, and it is expected to become a molecular target for inhibiting tumor progression.

Metabolic Engineering of Saccharomyces cerevisiae for Vitamin B5 Production.

Vitamin B5, also called d-pantothenic acid, is an essential vitamin in the human body and is widely used in pharmaceuticals, nutritional supplements, food, and cosmetics. However, few studies have investigated the microbial production of d-pantothenic acid, especially in Saccharomyces cerevisiae. By employing a systematic optimization strategy, we screened seven key genes in d-pantothenic acid biosynthesis from diverse species, including bacteria, yeast, fungi, algae, plants, animals, etc., and constructed an efficient heterologous d-pantothenic acid pathway in S. cerevisiae. By adjusting the copy number of the pathway modules, knocking out the endogenous bypass gene, balancing NADPH utilization, and regulating the GAL inducible system, a high-yield d-pantothenic acid-producing strain, DPA171, which can regulate gene expression using glucose, was constructed. By optimizing fed-batch fermentation, DPA171 produced 4.1 g/L d-pantothenic acid, which is the highest titer in S. cerevisiae to date. This study provides guidance for the development of vitamin B5 microbial cell factories.

METTL3 depletion contributes to tumour progression and drug resistance via N6 methyladenosine-dependent mechanism in HR+HER2-breast cancer.

BACKGROUND: Chemotherapy is an important strategy for the treatment of hormone receptor-positive/human epidermal growth factor receptor 2-negative (HR+HER2-) breast cancer (BC), but this subtype has a low response rate to chemotherapy. Growing evidence indicates that N6-methyladenosine (m6A) is the most common RNA modification in eukaryotic cells and that methyltransferase-like 3 (METTL3) participates in tumour progression in several cancer types. Therefore, exploring the function of METTL3 in HR+HER2- BC initiation and development is still important. METHODS: mRNA and protein expression levels were analysed by quantitative real-time polymerase chain reaction and western blotting, respectively. Cell proliferation was detected by CCK-8 and colony formation assays. Cell cycle progression was assessed by flow cytometry. Cell migration and invasion were analysed by wound healing assays and transwell assays, respectively, and apoptosis was analysed by TUNEL assays. Finally, m6A modification was analysed by methylated RNA immunoprecipitation. RESULTS: Chemotherapy-induced downregulation of the m6A modification is regulated by METTL3 depletion in HR+HER2- BC. METTL3 knockdown in MCF-7/T47D cells decreased the drug sensitivity of HR+HER2- BC cells by promoting tumour proliferation and migration and inhibiting apoptosis. Mechanistically, CDKN1A is a downstream target of METTL3 that activates the AKT pathway and promotes epithelial-mesenchymal transformation (EMT). Moreover, a decrease in BAX expression was observed when m6A modification was inhibited with METTL3 knockdown, and apoptosis was inhibited by the reduction of caspase-3/-9/-8. CONCLUSION: METTL3 depletion promotes the proliferation and migration and decreases the drug sensitivity of HR+HER2- BC via regulation of the CDKN1A/EMT and m6A-BAX/caspase-9/-3/-8 signalling pathways, which suggests METTL3 played a tumour-suppressor role and it could be a potential biomarker for predicting the prognosis of patients with HR+HER2- BC.

RNA-Seq-based transcriptomics analysis during the photodynamic therapy of primary cells in secondary hyperparathyroidism.

BACKGROUND: The aim of this study was to identify changes in gene expression before and after 5-aminolevulinic acid-mediated photodynamic therapy (5-ALA-PDT) and to investigate the potential mechanism of 5-ALA-PDT based on ribonucleic acid sequencing (RNA-Seq) analysis. METHODS: Secondary hyperparathyroidism (SHPT) primary cells were isolated from surgically excised specimens and exposed to laser light. The transcription profiles of SHPT primary cells were identified through RNA-Seq. Differentially expressed genes (DEGs) were identified. Enrichment of functions and signaling pathway analysis were performed based on Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses. Quantitative real-time polymerase chain reaction (RT-qPCR) and western blot analysis were used to validate genes based on RNA-Seq results. RESULTS: In total, 1320 DEGs were identified, of which 1019 genes were upregulated and 301 genes were downregulated. GO and KEGG pathway analyses identified significantly enriched pathways in DEGs, including TGF beta in extracellular matrix (ECM), negative regulation of triglyceride biosynthetic process, protein heterodimerization activity, systemic lupus erythematosus, ECM-receptor interaction, focal adhesion and protein digestion and absorption. Protein-protein interaction (PPI) network analyses identified potential heat shock protein (HSP) interactions among the DEGs. Eight HSP genes were also identified that were most likely involved in 5-ALA-PDT, which were further validated by RT-qPCR and western blotting. CONCLUSIONS: The findings of this descriptive study reveal changes in the transcriptome profile during 5-ALA-PDT, suggesting that gene expression and mutation, signaling pathways, and the molecular network are altered in SHPT primary cells. The above findings provide new insight for further studies on the mechanisms underlying 5-ALA-PDT in SHPT.

Deep learning-based multifeature integration robustly predicts central lymph node metastasis in papillary thyroid cancer.

BACKGROUND: Few highly accurate tests can diagnose central lymph node metastasis (CLNM) of papillary thyroid cancer (PTC). Genetic sequencing of tumor tissue has allowed the targeting of certain genetic variants for personalized cancer therapy development. METHODS: This study included 488 patients diagnosed with PTC by ultrasound-guided fine-needle aspiration biopsy, collected clinicopathological data, analyzed the correlation between CLNM and clinicopathological features using univariate analysis and binary logistic regression, and constructed prediction models. RESULTS: Binary logistic regression analysis showed that age, maximum diameter of thyroid nodules, capsular invasion, and BRAF V600E gene mutation were independent risk factors for CLNM, and statistically significant indicators were included to construct a nomogram prediction model, which had an area under the curve (AUC) of 0.778. A convolutional neural network (CNN) prediction model built with an artificial intelligence (AI) deep learning algorithm achieved AUCs of 0.89 in the training set and 0.78 in the test set, which indicated a high prediction efficacy for CLNM. In addition, the prediction models were validated in the subclinical metastasis and clinical metastasis groups with high sensitivity and specificity, suggesting the broad applicability of the models. Furthermore, CNN prediction models were constructed for patients with nodule diameters less than 1 cm. The AUCs in the training set and test set were 0.87 and 0.76, respectively, indicating high prediction efficacy. CONCLUSIONS: The deep learning-based multifeature integration prediction model provides a reference for the clinical diagnosis and treatment of PTC.

Corrigendum: Potential clinical impact of metagenomic next-generation sequencing of plasma for cervical spine injury with sepsis in ICU: A retrospective study.

[This corrects the article DOI: 10.3389/fcimb.2022.948602.].

Long-term nifekalant use in a patient with dilated cardiomyopathy and recurrent ventricular tachycardia.

The potential utility of nifekalant, a new Class III antiarrhythmic drug, to offer long-term protection against ventricular arrhythmia has been investigated in this case report. A 44-year-old male patient with dilated cardiomyopathy complicated with heart failure and persistent ventricular tachycardia was treated with nifekalant. The patient was treated with nifekalant for 31 days, which effectively terminated ventricular tachycardia and maintained sinus rhythm, with no clinical adverse reactions. After heart transplantation, postoperative follow-up showed good cardiac function and no arrhythmia. On the basis of nifekalant's working mechanism, there is a good chance that it can cure ventricular arrhythmia on a long-term basis.

Metabolic pathway assembly using docking domains from type I cis-AT polyketide synthases.

Engineered metabolic pathways in microbial cell factories often have no natural organization and have challenging flux imbalances, leading to low biocatalytic efficiency. Modular polyketide synthases (PKSs) are multienzyme complexes that synthesize polyketide products via an assembly line thiotemplate mechanism. Here, we develop a strategy named mimic PKS enzyme assembly line (mPKSeal) that assembles key cascade enzymes to enhance biocatalytic efficiency and increase target production by recruiting cascade enzymes tagged with docking domains from type I cis-AT PKS. We apply this strategy to the astaxanthin biosynthetic pathway in engineered Escherichia coli for multienzyme assembly to increase astaxanthin production by 2.4-fold. The docking pairs, from the same PKSs or those from different cis-AT PKSs evidently belonging to distinct classes, are effective enzyme assembly tools for increasing astaxanthin production. This study addresses the challenge of cascade catalytic efficiency and highlights the potential for engineering enzyme assembly.

Prognosis comparison between intraoperative radiotherapy and whole-breast external beam radiotherapy for T1-2 stage breast cancer without lymph node metastasis treated with breast-conserving surgery: A case-control study after propensity score matching.

Background: External beam radiotherapy (EBRT), an adjuvant to breast-conserving surgery (BCS), requires a long treatment period, is costly, and is associated with numerous complications. Large sample studies with long follow-up periods are lacking regarding whether intraoperative radiotherapy (IORT), an emerging radiotherapy modality, can replace EBRT for patients with T1-2 early stage breast cancer without lymph node metastasis treated with BCS. Methods: We identified 270,842 patients with T1-2N0M0 breast cancer from 2000 to 2018 in the Surveillance, Epidemiology, and End Results (SEER) database. A total of 10,992 patients were matched by propensity score matching (PSM). According to the radiotherapy method, the patients were divided into the IORT and EBRT groups. Overall survival (OS) and breast cancer-specific survival (BCSS) rates were analyzed and compared between the IORT and EBRT groups by Kaplan-Meier analysis. Bilateral P < 0.05 was considered to indicate significance. Results: After PSM, the survival analysis showed no significant differences in OS or BCSS rates between the IORT and EBRT groups. In the subgroup analysis, the IORT population diagnosed from 2010 to 2013 (HRs = 0.675, 95% CI 0.467-0.976, P = 0.037) or with T2 stage (HRs = 0.449, 95% CI 0.261-0.772, P = 0.004) had better OS rates, but in the overall population, the OS and BCSS rates were better in patients with T1 stage than in patients with T2 stage (P < 0.0001), and the proportion of chemotherapy was significantly higher in T2 stage than in T1 stage. Patients who had EBRT with unknown estrogen receptor had better OS rates (HRs = 3.392, 95% CI 1.368-8.407, P = 0.008). In addition, the IORT group had better BCSS rates for married (HRs = 0.403, 95% CI 0.184-0.881, P = 0.023), grade III (HRs = 0.405, 95% CI 0.173-0.952, P = 0.038), and chemotherapy-receiving (HRs = 0.327, 95% CI 0.116-0.917, P = 0.034) patients with breast cancer compared to the EBRT group. Conclusion: Intraoperative radiotherapy results of non-inferior OS and BCSS rates, compared to those of EBRT, in patients with early stage breast cancer without lymph node metastasis treated with BCS, and IORT may provide substantial benefits to patients as an effective alternative to standard treatment. This finding provides new insights into radiotherapy strategies for early stage breast cancer.

Potential clinical impact of metagenomic next-generation sequencing of plasma for cervical spine injury with sepsis in intensive care unit: A retrospective study.

Cervical spine injury (CSI) accounts for significant mortality in the intensive care unit (ICU), whereas sepsis remains one of the major causes of death in patients with CSI. However, there is no effective method to diagnose sepsis timely. The aim of this study is to investigate the effect of metagenomic next-generation sequencing (mNGS) on the pathogen features and the prognostic prediction of CSI patients with sepsis. A total of 27 blood samples from 17 included patients were tested by mNGS. Data of mNGS were compared with the conventional culture method. The Kaplan-Meier plots were used to visualize survival curves. A Cox proportional hazards model was used to identify independent prognostic factors for survival. Results showed that mNGS detected a wide spectrum of pathogens in CSI patients with sepsis, including 129 bacterial species, 8 viral species, and 51 fungal species. mNGS indicated 85.2% positive results, while the conventional culture method only showed 11.1% positive results in the blood samples. Further analyses revealed that mNGS had no prognostic effect on the septic CSI patients in ICU, whereas positive results of blood culture were closely correlated with an increased hazard ratio (HR) (HR 77.7067, 95%CI 2.860-2641.4595, p = 0.0155). Our results suggested that the mNGS application may provide evidence for clinicians to use antibiotics when a CSI case is diagnosed with sepsis.

3D reconstruction based novel methods are more effective than traditional clinical assessment in breast cancer axillary lymph node metastasis prediction.

The status of axillary lymph node metastases determines the treatment and overall survival of breast cancer (BC) patients. Three-dimensional (3D) assessment methods have advantages for spatial localization and are more responsive to morphological changes in lymph nodes than two-dimensional (2D) assessment methods, and we speculate that methods developed using 3D reconstruction systems have high diagnostic efficacy. This exploratory study included 43 patients with histologically confirmed BC diagnosed at Second Xiangya Hospital of Central South University between July 2017 and August 2020, all of whom underwent preoperative CT scans. Patients were divided into a training cohort to train the model and a validation cohort to validate the model. A 3D axillary lymph node atlas was constructed on a 3D reconstruction system to create various methods of assessing lymph node metastases for a comparison of diagnostic efficacy. Receiver operating characteristic (ROC) curve analysis was performed to assess the diagnostic values of these methods. A total of 43 patients (mean [SD] age, 47 [10] years) met the eligibility criteria and completed 3D reconstruction. An axillary lymph node atlas was established, and a correlation between lymph node sphericity and lymph node metastasis was revealed. By continuously fitting the size and characteristics of axillary lymph nodes on the 3D reconstruction system, formulas and models were established to determine the presence or absence of lymph node metastasis, and the 3D method had better sensitivity for axillary lymph node assessment than the 2D method, with a statistically significant difference in the correct classification rate. The combined diagnostic method was superior to a single diagnostic method, with a 92.3% correct classification rate for the 3D method combined with ultrasound. In addition, in patients who received neoadjuvant chemotherapy (NAC), the correct classification rate of the 3D method (72.7%) was significantly higher than that of ultrasound (45.5%) and CT (54.5%). By establishing an axillary lymph node atlas, the sphericity formula and model developed with the 3D reconstruction system achieve a high correct classification rate when combined with ultrasound or CT and can also be applied to patients receiving NAC.

Prognostic value of tumor mutation burden and the relationship between tumor mutation burden and immune infiltration in HER2+ breast cancer: a gene expression-based study.

BACKGROUND: Whether tumor mutation burden (TMB) correlated with improved survival outcomes or promotion of immunotherapies remained controversy in various malignancies. We aimed to explore the prognostic value of TMB and the relationship between TMB and immune infiltration in human epidermal growth factor receptor 2-positive (HER2+) breast cancer (BC). METHODS: We downloaded somatic mutation data and clinical information for 216 HER2+ BC patients from the The Cancer Genome Atlas (TCGA) and cBioPortal databases. Patients were divided into high- and low-TMB groups through TMB calculation. Cox regression analysis was used to establish an immune- and mutant-related risk model based on 5-hub genes. The relationship between 5-hub genes mutants and the level of immune infiltration, as well as the relationship between the risk model and the immune microenvironment were analyzed by "TIMER" database. RESULTS: TMB was negatively correlated with overall survival (OS) and disease-free survival (DFS), and high TMB may inhibit immune infiltration in HER2+ BC. Furthermore, risk score classified effectively patients into low- and high-risk groups in training and validation cohorts. The infiltration of CD4+ T cells and NK cells and the levels of immune checkpoint pathway genes were lower in the high-risk group, which indicated a poor prognosis. CONCLUSIONS: Higher TMB correlated with poor survival outcomes and might inhibit the immune infiltrates in HER2+ BC. The 5-hub TMB-related signature conferred lower immune cells infiltration which deserved further validation.

Construction and validation of a risk prediction model for clinical axillary lymph node metastasis in T1-2 breast cancer.

The current diagnostic technologies for assessing the axillary lymph node metastasis (ALNM) status accurately in breast cancer (BC) remain unsatisfactory. Here, we developed a diagnostic model for evaluating the ALNM status using a combination of mRNAs and the T stage of the primary tumor as a novel biomarker. We collected relevant information on T1-2 BC from public databases. An ALNM prediction model was developed by logistic regression based on the screened signatures and then internally and externally validated. Calibration curves and the area under the curve (AUC) were employed as performance metrics. The prognostic value and tumor immune infiltration of the model were also determined. An optimal diagnostic model was created using a combination of 11 mRNAs and T stage of the primary tumor and showed high discrimination, with AUCs of 0.828 and 0.746 in the training sets. AUCs of 0.671 and 0.783 were achieved in the internal validation cohorts. The mean external AUC value was 0.686 and ranged between 0.644 and 0.742. Moreover, the new model has good specificity in T1 and hormone receptor-negative/human epidermal growth factor receptor 2- negative (HR-/HER2-) BC and good sensitivity in T2 BC. In addition, the risk of ALNM and 11 mRNAs were correlated with the infiltration of M2 macrophages, as well as the prognosis of BC. This novel prediction model is a useful tool to identify the risk of ALNM in T1-2 BC patients, particularly given that it can be used to adjust surgical options in the future.

Chemotherapy significantly improves long-term survival of small lesion node negative metaplastic breast carcinoma in T1c population rather than T1a and T1b.

Metaplastic breast carcinoma (MpBC) is considered a highly aggressive disease, the outcome of chemotherapy on small lesions (T1abcN0M0) MpBC patients remain unclear. We identified 890 female MpBC patients in the Surveillance, Epidemiology, and End Results (SEER) database from 2000 to 2016. After propensity score matching (PSM), 584 patients were matched. Survival probability was compared among T1a, T1b, and T1c patients and between patients with and without chemotherapy using Kaplan-Meier analysis and Cox proportional hazard analysis. Significance was set at two-sided P < 0.05. We classified 49, 166, and 675 patients as T1a, T1b, and T1c MpBC, respectively. The chemotherapy group included 404 patients (45.4%). Following PSM, survival analysis indicated that the patients who underwent chemotherapy had higher OS (P = 0.0002) and BCSS (P = 0.0276) in the T1c substage, but no significant difference was detected in T1a or T1b patients. In this population-based study, small lesion MpBC showed a favorable prognosis. Chemotherapy improved the prognosis of T1c MpBC patients but not T1a and T1b patients to a beneficial extent. Our findings may offer novel insight into a therapeutic strategy for MpBC.