Currently, the clinical diagnosis and treatment for invasive lobular carcinoma of the breast (ILC) often draw on the treatment approaches used for invasive ductal carcinoma (IDC), despite significant differences between the two. Studies evaluating the risk and prognosis of ILC are limited; thus, our goal was to construct a predictive model for the prognosis of ILC. Clinical data of patients diagnosed with unilateral primary ILC from 2010 to 2015 were acquired from the SEER database. Independent prognostic factors affecting patients’ overall survival (OS) and cancer-specific survival (CSS) were determined through univariate and multivariate analyses based on COX proportional hazards model and Fine-Gray competing risks model. Nomograms were constructed to forecast the 1-year, 3-year, and 5-year OS and CSS of the patients. A total of 6,616 patients with ILC were included, with 1,083 deaths, of which 541 were attributed to ILC, and 542 to other causes. The univariate and multivariate analyses indicated that age, N stage, stage, surgery, PR status, radiotherapy, and brain metastasis are independent risk factors for OS of ILC patients, while age, N stage, stage, surgery, PR status, and brain metastasis are independent risk factors for CSS of ILC patients. The C-index, area under the ROC curve, and calibration curve of the 1-, 3-, and 5-year OS and CSS prediction models confirmed that it had good predictive capability. This study has developed subtype-specific predictive models for OS and CSS of patients with ILC, offering clinicians a regimen. Reference for assessing patient prognosis and formulating individualized treatment.

Cancer, the second-leading cause of mortality, kills 16% of people worldwide. Unhealthy lifestyles, smoking, alcohol abuse, obesity, and a lack of exercise have been linked to cancer incidence and mortality. However, it is hard. Cancer and lifestyle correlation analysis and cancer incidence and mortality prediction in the next several years are used to guide people's healthy lives and target medical financial resources. Two key research areas of this paper are Data preprocessing and sample expansion design Using experimental analysis and comparison, this study chooses the best cubic spline interpolation technology on the original data from 32 entry points to 420 entry points and converts annual data into monthly data to solve the problem of insufficient correlation analysis and prediction. Factor analysis is possible because data sources indicate changing factors. TSA-LSTM Two-stage attention design a popular tool with advanced visualization functions, Tableau, simplifies this paper's study. Tableau's testing findings indicate it cannot analyze and predict this paper's time series data. LSTM is utilized by the TSA-LSTM optimization model. By commencing with input feature attention, this model attention technique guarantees that the model encoder converges to a subset of input sequence features during the prediction of output sequence features. As a result, the model's natural learning trend and prediction quality are enhanced. The second step, time performance attention, maintains We can choose network features and improve forecasts based on real-time performance. Validating the data source with factor correlation analysis and trend prediction using the TSA-LSTM model Most cancers have overlapping risk factors, and excessive drinking, lack of exercise, and obesity can cause breast, colorectal, and colon cancer. A poor lifestyle directly promotes lung, laryngeal, and oral cancers, according to visual tests. Cancer incidence is expected to climb 18-21% between 2020 and 2025, according to 2021. Long-term projection accuracy is 98.96 percent, and smoking and obesity may be the main cancer causes.

Objectives: Triple-negative breast cancer (TNBC) presents a major treatment challenge due to its aggressive behavior. The dysfunction of the Golgi apparatus (GA) contributes to the development of various cancers. This study aimed to utilize GA-related genes (GARGs) to forecast the prognosis and immune profile of TNBC. Methods: The data were downloaded from The Cancer Genome Atlas (TCGA) database, including 175 TNBC and 99 healthy samples. The differentially expressed GARGs (DEGARGs) were analyzed using the TCGA biolinks package. The patients with TNBC were classified into two clusters utilizing the ConsensusClusterPlus package according to prognosis-related DEGARGs, followed by comparing the differences in prognosis and immune infiltration between the two clusters. Next, LASSO and stepwise Cox regression were applied to establish a GARGs signature to forecast the TNBC prognosis. The association of the GARGs signature with immune infiltrates and drug sensitivity was further explored. Results: In total, 430 DEGARGs were identified between TNBC and healthy samples, among which 20 were related to TNBC prognosis. Two GARG-related molecular clusters associated with different survival times and immune heterogeneity were identified. A risk model for TNBC was established based on six GARGs, and the high-risk (HR) group exhibited a poor prognosis. The HR group demonstrated a distinctly high M2 macrophage infiltration and low M1 macrophage infiltration, which contributed to an immunosuppressive tumor microenvironment and thus led to poor prognosis of the HR group. Immune dysfunction scores and programmed cell death ligand 1 (PD-L1) expression were substantially elevated in the HR group. The HR group showed increased sensitivity to anticancer drugs, such as cisplatin. Conclusion: Our findings suggest that GARGs are involved in the pathogenesis of TNBC and provide new insights into prognostic prediction. The identified clusters and GARGs signatures have the potential to guide individualized therapy.

Cancer cells rely on aerobic glycolysis and DNA repair signals to drive tumor growth and develop drug resistance. Yet, fine-tuning aerobic glycolysis with the assist of nanotechnology, for example, dampening lactate dehydrogenase (LDH) for cancer cell metabolic reprograming remains to be investigated. Here we focus on anaplastic thyroid cancer (ATC) as an extremely malignant cancer with the high expression of LDH, and develop a pH-responsive and nucleus-targeting platinum nanocluster (Pt@TAT/sPEG) to simultaneously targets LDH and exacerbates DNA damage. Pt@TAT/sPEG effectively disrupts LDH activity, reducing lactate production and ATP levels, and meanwhile induces ROS production, DNA damage, and apoptosis in ATC tumor cells. We found Pt@TAT/sPEG also blocks nucleotide excision repair pathway and achieves effective tumor cell killing. In an orthotopic ATC xenograft model, Pt@TAT/sPEG demonstrates superior tumor growth suppression compared to Pt@sPEG and cisplatin. This nanostrategy offers a feasible approach to simultaneously inhibit glycolysis and DNA repair for metabolic reprogramming and enhanced tumor chemotherapy.

Background:In the context of head-and-neck squamous cell carcinoma (HNSCC), dendritic cells (DCs) assume pivotal responsibilities, acting as architects of antigen presentation and conductors of immune checkpoint modulation. In this study, we aimed to identify hub genes associated with DCs in HNSCC and explore their prognostic significance and implications for immunotherapy. Methods:Integrated clinical datasets from The Cancer Genome Atlas (TCGA)-HNSCC and GSE65858 cohorts underwent meticulous analysis. Employing weighted gene co-expression network analysis (WGCNA), we delineated candidate genes pertinent to DCs. Through the application of random survival forest and least absolute shrinkage and selection operator (LASSO) Cox's regression, we derived key genes of significance. Lisa (epigenetic Landscape In Silico deletion Analysis and the second descendent of MARGE) highlighted transcription factors, with Dual-luciferase assays confirming their regulatory role. Furthermore, immunotherapeutic sensitivity was assessed utilizing the Tumor Immune Dysfunction and Exclusion online tool. Results:This study illuminated the functional intricacies of HNSCC DC subsets to tailor innovative therapeutic strategies. We leveraged clinical data from the TCGA-HNSCC and GSE65858 cohorts. We subjected the data to advanced analysis, including WGCNA, which revealed 222 DC-related candidate genes. Following this, a discerning approach utilizing random survival forest analysis and LASSO Cox's regression unveiled seven genes associated with the prognostic impact of DCs, notably ACP2 and CPVL, associated with poor overall survival. Differential gene expression analysis between ACP2 + and ACP2 - DC cells revealed 208 differential expressed genes. Lisa analysis identified the top five significant transcription factors as STAT1, SPI1, SMAD1, CEBPB, and IRF1. The correlation between STAT1 and ACP2 was confirmed through quantitative reverse transcription polymerase chain reaction (qRT-PCR) and Dual-luciferase assays in HEK293T cells. Additionally, TP53 and FAT1 mutations were more common in high-risk DC subgroups. Importantly, the sensitivity to immunotherapy differed among the risk clusters. The low-risk cohorts were anticipated to exhibit favorable responses to immunotherapy, marked by heightened expressions of immune system-related markers. In contrast, the high-risk group displayed augmented proportions of immunosuppressive cells, suggesting a less conducive environment for immunotherapeutic interventions. Conclusions:Our research may yield a robust DC-based prognostic system for HNSCC; this will aid personalized treatment and improve clinical outcomes as the battle against this challenging cancer continues.

Sepsis is a clinical syndrome caused by infection, leading to organ dysfunction due to a dysregulated host response. In recent years, its high mortality rate has made it a significant cause of death and disability worldwide. The pathophysiological process of sepsis is related to the body’s dysregulated response to infection, with microcirculatory changes serving as early warning signals that guide clinical treatment. The Peripheral Perfusion Index (PI), as an indicator of peripheral microcirculation, can effectively evaluate patient prognosis. This study aims to develop two new prediction models using PI and other common clinical indicators to assess the mortality risk of sepsis patients during hospitalization and within 28 days post-ICU admission. This retrospective study analyzed data from sepsis patients treated in the Intensive Care Unit of Peking Union Medical College Hospital between December 2019 and June 2023, ultimately including 645 patients. LASSO regression and logistic regression analyses were used to select predictive factors from 35 clinical indicators, and two clinical prediction models were constructed to predict in-hospital mortality and 28-day mortality. The models’ performance was then evaluated using ROC curve, calibration curve, and decision curve analyses. The two prediction models performed excellently in distinguishing patient mortality risk. The AUC for the in-hospital mortality prediction model was 0.82 in the training set and 0.73 in the validation set; for the 28-day mortality prediction model, the AUC was 0.79 in the training set and 0.73 in the validation set. The calibration curves closely aligned with the ideal line, indicating consistency between predicted and actual outcomes. Decision curve analysis also demonstrated high net benefits for the clinical utility of both models. The study shows that these two prediction models not only perform excellently statistically but also hold high practical value in clinical applications. The models can help physicians accurately assess the mortality risk of sepsis patients, providing a scientific basis for personalized treatment.

Breast cancer (BC) is the most common cancer affecting women and the leading cause of cancer-related deaths worldwide. Compelling evidence indicates that pyroptosis is inextricably involved in the development of cancer and may activate tumor-specific immunity and/or enhance the effectiveness of existing therapies. We constructed a novel prognostic prediction model for BC, based on pyroptosis-related clusters, according to RNA-seq and clinical data downloaded from TCGA. The proportions of tumor-infiltrating immune cells differed significantly in the two pyroptosis clusters, which were determined according to 38 pyroptosis-related genes, and the immune-related pathways were activated according to GO and KEGG enrichment analysis. A 56-gene signature, constructed using univariate and multivariate Cox regression, was significantly associated with progression-free interval (PFI), disease-specific survival (DSS), and overall survival (OS) of patients with BC. Cox analysis revealed that the signature was significantly associated with the PFI and DSS of patients with BC. The signature could efficiently distinguish high- and low-risk patients and exhibited high sensitivity and specificity when predicting the prognosis of patients using KM and ROC analysis. Combined with clinical risk, patients in both the gene and clinical low-risk subgroup who received adjuvant chemotherapy had a significantly lower incidence of the clinical event than those who did not. This study presents a novel 56-gene prognostic signature significantly associated with PFI, DSS, and OS in patients with BC, which, combined with the TNM stage, might be a potential therapeutic strategy for individualized clinical decision-making.

BACKGROUND:Breast cancer patients who are positive for hormone receptor typically exhibit a favorable prognosis. It is controversial whether chemotherapy is necessary for them after surgery. Our study aimed to establish a multigene model to predict the relapse of hormone receptor-positive early-stage Chinese breast cancer after surgery and direct individualized application of chemotherapy in breast cancer patients after surgery. METHODS:In this study, differentially expressed genes (DEGs) were identified between relapse and nonrelapse breast cancer groups based on RNA sequencing. Gene set enrichment analysis (GSEA) was performed to identify potential relapse-relevant pathways. CIBERSORT and Microenvironment Cell Populations-counter algorithms were used to analyze immune infiltration. The least absolute shrinkage and selection operator (LASSO) regression, log-rank tests, and multiple Cox regression were performed to identify prognostic signatures. A predictive model was developed and validated based on Kaplan-Meier analysis, receiver operating characteristic curve (ROC). RESULTS:A total of 234 out of 487 patients were enrolled in this study, and 1588 DEGs were identified between the relapse and nonrelapse groups. GSEA results showed that immune-related pathways were enriched in the nonrelapse group, whereas cell cycle- and metabolism-relevant pathways were enriched in the relapse group. A predictive model was developed using three genes ( CKMT1B , SMR3B , and OR11M1P ) generated from the LASSO regression. The model stratified breast cancer patients into high- and low-risk subgroups with significantly different prognostic statuses, and our model was independent of other clinical factors. Time-dependent ROC showed high predictive performance of the model. CONCLUSIONS:A multigene model was established from RNA-sequencing data to direct risk classification and predict relapse of hormone receptor-positive breast cancer in Chinese patients. Utilization of the model could provide individualized evaluation of chemotherapy after surgery for breast cancer patients.

Additional file 16: Table S5. The Algorithms and Variables Incorporated in the Risk Prediction Models.

The advancement in systemic neoadjuvant therapy has significantly increased the pathological complete response (pCR) rate in breast cancer. As surgeries inevitably affect patients physically and psychologically and the accuracy of pCR prediction and diagnosis by minimal invasive biopsy is improving, the necessity of surgery in neoadjuvant chemotherapy (NAC) patients who achieve pCR is under debate. Thus, we conducted a literature review of studies on the selective omission of breast surgery after NAC for breast cancer patients. We summarized the existing predictive models and technologies to predict and diagnose pCR after NAC. Our research indicates that, for nearly half a century, the extent of surgery on both breast and axillary lymph nodes is decreasing, while more precise systematic treatments are increasing. NAC has advanced significantly and its pCR rates have improved, so surgery may be omitted in certain patients. However, accurately predicting pCR after NAC is still a challenge. We also described the design for a randomized clinical trial and the potential problems of omitting surgical treatment after NAC. In summary, the decrease in breast cancer surgery is an unavoidable trend, and more high-quality clinical trials need to be conducted.

Background: BRCA1/2 mutation carriers are suggested with regular breast cancer surveillance screening strategies using mammography with supplementary MRI as an adjunct tool in Western countries. From a cost-effectiveness perspective, however, the benefits of screening modalities remain controversial among different mutated genes and screening schedules. Methods: We searched the MEDLINE/PubMed, Embase, Cochrane Library, Scopus, and Web of Science databases to collect and compare the results of different cost-effectiveness analyses. A simulated model was used to predict the impact of screening strategies in the target group on cost, life-year gained, quality-adjusted life years, and incremental cost-effectiveness ratio (ICER). Results:Nine cost-effectiveness studies were included. Combined mammography and MRI strategy is cost-effective in BRCA1 mutation carriers for the middle-aged group (age 35 to 54). BRCA2 mutation carriers are less likely to benefit from adjunct MRI screening, which implies that mammography alone would be sufficient from a cost-effectiveness perspective, regardless of dense breast cancer. Conclusions: Precision screening strategies among BRCA1/2 mutation carriers should be conducted according to the acceptable ICER, i.e., a combination of mammography and MRI for BRCA1 mutation carriers and mammography alone for BRCA2 mutation carriers. Systematic Review RegistrationPROSPERO, identifier CRD42020205471.

近年来,以假体为基础的乳房重建术蓬勃发展,乳房假体植入后乳房相关肿瘤日益多发,尤其是乳房假体相关间变性大细胞淋巴瘤(BIA-ALCL)发生率逐步增高,主要临床表现为伴血清肿的乳房肿胀、乳房肿物及淋巴结肿大.发病机制尚不明确,可能与慢性炎症刺激、毛面假体诱发、免疫反应及某些病原体感染有关.常用的诊断方法有乳腺超声检查、假体周围渗液的细胞学检查、免疫表型检查及乳房肿块的组织活检.治疗方法主要依靠手术治疗.本文对乳房假体植入后发生相关肿瘤的文献进行了系统回顾和综述,以期引起临床医生的警惕和思考.

A proportion of up to 10% of breast cancer resulted from hereditary germline pathogenic variants (GPVs) in cancer predisposition genes (CPGs), which been demonstrated distinct clinical features and imaging manifestations. However, the performance of imaging modalities for breast cancer surveillance in CPG mutation-carriers is still unclear, especially in Asian women. A population of 3002 breast cancer patients who received germline genetic testing of CPGs was enrolled from three hospitals in China. In total, 343 (11.6%) patients were found to harbor GPVs in CPGs, including 137 (4.6%) in BRCA1 and 135 (4.6%) in BRCA2. We compared the performances of ultrasound, mammograms, MRI, and the combining strategies in CPG mutation carriers and non-carriers. As a result, the ultrasound showed a higher detection rate compared with mammograms regardless of the mutation status. However, its detection rate was lower in CPG mutation carriers than in non-carriers (93.2% vs 98.0%, P=2.1×10-4), especially in the BRCA1 mutation carriers (90.9% vs 98.0%, P=2.0×10-4). MRI presented the highest sensitivity (98.5%) and the lowest underestimation rate (14.5%) in CPG mutation carriers among ultrasound, mammograms, and their combination. Supplemental ultrasound or mammograms would add no significant value to MRI for detecting breast cancer (P>0.05). In multivariate logistic regression analysis, the family or personal cancer history could not replace the mutation status as the impact factor for the false-negative result and underestimation. In summary, clinicians and radiologists should be aware of the atypical imaging presentation of breast cancer in patients with GPVs in CPGs.

As the highest incidence of female malignancy, breast cancer is likewise the leading cause of cancer-related deaths. The development of cancer relies on neo-vascularization, which provides sufficient nutrition and oxygen, and supplies a pathway for distant metastasis. Angiogenesis represents the formation of new blood vessels, and is a principal pathogenetic action in breast cancer. Vascular endothelial growth factor (VEGF) is a major angiogenesis regulator that modulates the maintenance and function of mature vascular networks. Therefore, the VEGF pathway is a promising oncotherapeutic target. This review elaborates an update on the prognostic value of VEGF in breast cancer, summarizes clinical experience and lessons of anti-VEGF therapeutics, meanwhile, provides an overview of biomarkers that predict the effectiveness of anti-angiogenic treatment.

乳腺癌的发病率逐年增高,对女性身心健康造成严重影响,引起社会广泛关注.改善乳腺癌预后的根本在于早期诊断、早期治疗.乳腺超声、钼靶、CT和MRI等影像学检查手段在乳腺癌的早期诊断中发挥了重要的作用.随着分子生物学的发展,众多分子标志物被发现对于乳腺癌的早期诊断更具临床意义,并有良好的应用前景.全文综述乳腺癌的诊断技术,希望给临床医生提供参考.

乳腺癌是在女性疾病中致死率第二高的恶性肿瘤,其治疗包括手术、化疗、放疗、内分泌治疗等.但是,各种并发症也伴随乳腺癌的治疗而产生,其中,最常见的是淋巴水肿,以及可能发生肩和手臂活动受限. 渐进的淋巴水肿 为消灭已转移至患者腋部淋巴结的癌细胞,乳腺癌手术会切除2个或3个淋巴结(即行前哨淋巴结活检,SLNB),或更多(10 ～ 40个)淋巴结(即行腋窝淋巴结清扫,ALND),因为癌细胞最有可能首先进入离乳房邻近的腋下淋巴结.

CircRNA mitochondrial tRNA translation optimization 1 (circMTO1) functions as a tumor suppressor usually and is related to the progression of many tumors, including hepatocellular carcinoma (HCC). CircMTO1 is downregulated in HCC as compared to adjacent nontumor tissue, which may suppress the HCC progression by certain signal pathways. However, the underlying signal pathway remains largely unknown. The interactions between circMTO1 and miR-541-5p were predicted through bioinformatics analysis and verified using pull-down and dual-luciferase reporter assays. CCK-8, transwell, and apoptosis assays were performed to determine the effect of miR-541-5p on HCC progression. Using bioinformatic analysis, dual-luciferase reporter assay, RT-qPCR, and western blot, ZIC1 was found to be the downstream target gene of miR-541-5p. The regulatory mechanisms of circMTO1, miR-541-5p, and ZIC1 were investigated using in vitro and in vivo rescue experiments. The results depicted that silencing circMTO1 or upregulating miR-541-5p expression facilitated HCC cell proliferation, migration, and invasion and inhibited apoptosis. CircMTO1 silencing upregulated the expression of downstream ZIC1 regulators of the Wnt/β-catenin pathway markers, β-catenin, cyclin D1, c-myc, and the mesenchymal markers N-cadherin, Vimentin, and MMP2, while the epithelial marker E-cadherin was downregulated. MiR-541-5p knockdown had the opposite effect and reversed the effect of circMTO1 silencing on the regulation of downstream ZIC1 regulators. Intratumoral injection of miR-541-5p inhibitor suppressed tumor growth and reversed the effect of circMTO1 silencing on the promotion of tumor growth in HCC. These findings indicated that circMTO1 suppressed HCC progression via the circMTO1/ miR-541-5p/ZIC1 axis by regulating Wnt/β-catenin signaling and epithelial-to-mesenchymal transition, making it a novel therapeutic target.

Breast cancer (BC) is the most common cancer affecting women and the leading cause of cancer-related deaths worldwide. Compelling evidence indicates that microRNAs (miRNAs) are inextricably involved in the development of cancer. Here, we constructed a novel model, based on miRNA-seq and clinical data downloaded from The Cancer Genome Atlas (TCGA). Data from a total of 962 patients were included in this study, and the relationships among their clinicopathological features, survival, and miRNA-seq expression levels were analyzed. Hsa-miR-186 and hsa-miR-361 were identified as internal reference miRNAs and used to normalize miRNA expression data. A five-miRNA signature, constructed using univariate and multivariate Cox regression, was significantly associated with disease-specific survival (DSS) of patients with BC. Kaplan–Meier (KM) and receiver operating characteristic (ROC) analyses were conducted to confirm the clinical significance of the five-miRNA signature. Finally, a nomogram was constructed based on the five-miRNA signature to evaluate its clinical value. Cox regression analysis revealed that a five-miRNA signature was significantly associated with DSS of patients with BC. KM analysis demonstrated that the signature could efficiently distinguish high- and low-risk patients. Moreover, ROC analysis showed that the five-miRNA signature exhibited high sensitivity and specificity in predicting the prognosis of patients with BC. Patients in the high-risk subgroup who received adjuvant chemotherapy had a significantly lower incidence of mortality than those who did not. A nomogram constructed based on the five-miRNA signature was effective in predicting 5-year DSS. This study presents a novel five-miRNA signature as a reliable prognostic tool to predict DSS and provide theoretical reference significance for individualized clinical decisions for patients with BC.

Sentinel lymph node (LN) biopsy is currently the standard procedure for clinical LN‐negative breast cancer (BC) patients but it is prone to false‐negative results and complications. Thus, an accurate noninvasive approach for LN staging is urgently needed in clinical practice. Here, circulating exosomal microRNA (miRNA) expression profiles in peripheral blood from BC patients and age‐matched healthy women were obtained and analyzed. We identified an exosomal miRNA,miR‐363‐5p, that was significantly downregulated in exosomes from plasma of BC patients with LN metastasis which exhibited a consistent decreasing trend in tissue samples from multiple independent datasets. Plasma exosomalmiR‐363‐5pachieved high diagnostic performance in distinguishing LN‐positive patients from LN‐negative patients. The highmiR‐363‐5p expressionlevel was significantly correlated with improved overall survival. Functional assays demonstrated that exosomalmiR‐363‐5pmodulates platelet‐derived growth factor (PDGF) signaling activity by targeting PDGFB to inhibit cell proliferation and migration. Our study revealed, for the first time, plasma exosomalmiR‐363‐5pplays a tumor suppressor role in BC and has the potential for noninvasive LN staging and prognosis prediction of BC.