PIK3CA mutation-driven immune signature as a prognostic marker for evaluating the tumor immune microenvironment and therapeutic response in breast cancer.

PURPOSE: Gene mutations drive tumor immune microenvironment (TIME) heterogeneity, in turn affecting prognosis and immunotherapy efficacy. PIK3CA is the most frequently mutated gene in breast cancer (BC), yet its relevance to BC prognosis remains controversial. Herein, we sought to determine the impact of PIK3CA mutation-driven immune genes (PDIGs) on BC prognosis in relation to TIME heterogeneity. METHODS: PIK3CA mutation characteristics were compared and verified between the TCGA-BRCA dataset and a patient cohort from our hospital. PIK3CA mutation-driven differentially expressed genes were identified for consensus clustering and weighted gene co-expression network analysis to select the modules most relevant to the immune subtype. Thereafter, the two were intersected to obtain PDIGs. Univariate Cox, LASSO, and multivariate Cox regression analyses were sequentially performed on PDIGs to obtain a PIK3CA mutation-driven immune signature (PDIS), which was then validated using the Gene Expression Omnibus (GEO) database. Differences in functional enrichment, mutation landscape, immune infiltration, checkpoint gene expression, and drug response were compared between different risk groups. RESULTS: PIK3CA mutation frequencies in the TCGA and validation cohorts were 34.49% and 40.83%, respectively. PIK3CA mutants were significantly associated with ER, PR, and molecular BC subtypes in our hospital cohort. The PDIS allowed for effective risk stratification and exhibited prognostic power in TCGA and GEO sets. The low-risk patients exhibited greater immune infiltration, higher expression of common immune checkpoint factors, and lower scores for tumor immune dysfunction and exclusion. CONCLUSION: The PDIS can be used as an effective prognostic model for predicting immunotherapy response to guide clinical decision-making.

Effect of T Stages on the Choice of Axillary Evaluation Modality in Breast Cancer Patients With 1-2 Sentinel Lymph Node Metastases.

INTRODUCTION: The survival benefit of axillary lymph node dissection (ALND), sentinel lymph node biopsy (SLNB) combined with radiation, and ALND combined with radiation remains unclear in breast cancer (BC) patients with 1-2 metastatic sentinel lymph nodes (SLNs). This study aims to rigorously evaluate the prognostic impact of these axillary evaluation modalities on BC patients with varying T-stages and to construct a survival prediction nomogram. METHODS: Following screening for inclusion and exclusion criteria, data pertaining to BC patients were extracted from the SEER database. Overall survival (OS) and breast cancer-specific survival (BCSS) were assessed using Kaplan-Meier curves and Cox proportional hazards model among patients with different stages who underwent various axillary evaluation modalities. A nomogram was constructed to predict the probability of OS and BCSS. RESULTS: A total of 20,283 patients were included, comprising 9626 who underwent breast-conserving surgery (BCS) and 10,657 who underwent mastectomy. In the T4 stage stratified analysis, both BCS and mastectomy groups exhibited superior OS and BCSS with ALND compared to SLNB combined with radiation. Further, ALND combined with radiation improved OS. However, for T1-3 stages, patients treated with ALND experienced similar or worse survival compared to those treated with SLNB combined with radiation. The calibration curve and C-index (0.746-0.794) of the nomogram demonstrated the efficacy of the survival prediction model. CONCLUSION: In T1-3 BC patients with 1-2 metastatic SLNs, SLNB combined with radiation is a safe alternative to ALND. Conversely, for T4 patients, ALND combined with radiation may offer a preferable choice.

Development and validation of a nomogram for predicting the early death of anaplastic thyroid cancer: a SEER population-based study.

BACKGROUND: Anaplastic thyroid cancer (ATC) is a highly aggressive malignancy with dismal prognosis. This study aimed to identify the independent risk factors and construct a readily-to-use nomogram to predict the probability of early death in ATC patients. METHOD: Patients diagnosed with ATC between 2004 and 2015 from the Surveillance, Epidemiology, and End Results (SEER) database were enrolled in this study for model development and internal validation. Univariate and multivariate logistic regression analyses were conducted to identify independent risk factors for early death of ATC. Nomograms for predicting the probability of all-cause early death (ACED) and cancer-specific early death (CSED) of ATC were subsequently developed. The performance of the nomograms was comprehensively evaluated and validated in an internal cohort. RESULT: A total of 696 ATC patients were included in this study, of which 488 patients in the training cohort and 208 patients in the validation cohort. The univariate and multivariate logistic regression analyses identified five independent factors (tumor size, M stage, surgery, radiotherapy and chemotherapy) in the ACED model and six variables in the CSED (gender, tumor size, M stage, surgery, radiotherapy and chemotherapy) model for the establishment of the nomograms. Calibration curves and receiver operating characteristic (ROC) curves showed satisfactory efficacy and consistency both in the training (ACED: AUC values: 0.814 (0.776-0.852); CSED: 0.778 (0.736-0.820)) and validation sets (ACED: 0.762 (0.696-0.827); CSED: 0.745 (0.678-0.812)). In addition, the decision curve analysis (DCA) demonstrated the favorable potential of the two nomograms in clinical application. CONCLUSION: The two nomograms assist clinicians to identify risk factors and predict the early death probability among ATC patients, thus guide individualized treatment to improve the prognosis.

Prognostic value and mode selection of locoregional treatment in Stage-IV breast cancer patients.

PURPOSE: This study aimed to assess the actual prognostic significance of different locoregional treatment (LRT) (surgery and radiotherapy) modalities for stage-IV  breast cancer (BC) patients and construct a competing risk nomogram to make precise predictions of the breast cancer-specific death (BCSD) risk among LRT recipients. METHODS: A total of 9279 eligible stage-IV BC patients from the Surveillance Epidemiology and End Results (SEER) database were included in this study. Initially, we evaluated the impact of LRT on survival both before and after the propensity score matching (PSM). Then, we used the Cox hazard proportional model and competing risk model to identify the independent prognostic factors for LRT recipients. Based on the screened variables, a comprehensive nomogram was established. RESULTS: Kaplan-Meier curves demonstrated that LRT significantly prolonged overall survival (OS) and breast cancer-specific survival (BCSS) (P < 0.001). In addition, patients treated with surgery combined with postoperative radiotherapy (PORT) possessed the optimal survival (P < 0.001). Regardless of the surgical modalities, primary tumor resection combined with radiotherapy could ameliorate the prognosis (P < 0.05). Subgroup analysis showed that in patients with T2-T4 stage, PORT had a survival benefit compared with those undergoing surgery combined with preoperative radiotherapy (PRRT) and surgery only. Based on the screened independent prognostic factors, we established a comprehensive nomogram to forecast BCSD in 1 year, 2 years and 3 years, which showed robust predictive ability. CONCLUSION: PORT was associated with a lower BCSD in stage-IV BC patients. The practical nomogram could provide a precise prediction of BCSD for LRT recipients, which was meaningful for patients' individualized management.

Comprehensive analysis of nicotinamide metabolism-related signature for predicting prognosis and immunotherapy response in breast cancer.

Background: Breast cancer (BC) is the most common malignancy among women. Nicotinamide (NAM) metabolism regulates the development of multiple tumors. Herein, we sought to develop a NAM metabolism-related signature (NMRS) to make predictions of survival, tumor microenvironment (TME) and treatment efficacy in BC patients. Methods: Transcriptional profiles and clinical data from The Cancer Genome Atlas (TCGA) were analyzed. NAM metabolism-related genes (NMRGs) were retrieved from the Molecular Signatures Database. Consensus clustering was performed on the NMRGs and the differentially expressed genes between different clusters were identified. Univariate Cox, Lasso, and multivariate Cox regression analyses were sequentially conducted to develop the NAM metabolism-related signature (NMRS), which was then validated in the International Cancer Genome Consortium (ICGC) database and Gene Expression Omnibus (GEO) single-cell RNA-seq data. Further studies, such as gene set enrichment analysis (GSEA), ESTIMATE, CIBERSORT, SubMap, and Immunophenoscore (IPS) algorithm, cancer-immunity cycle (CIC), tumor mutation burden (TMB), and drug sensitivity were performed to assess the TME and treatment response. Results: We identified a 6-gene NMRS that was significantly associated with BC prognosis as an independent indicator. We performed risk stratification according to the NMRS and the low-risk group showed preferable clinical outcomes (P < 0.001). A comprehensive nomogram was developed and showed excellent predictive value for prognosis. GSEA demonstrated that the low-risk group was predominantly enriched in immune-associated pathways, whereas the high-risk group was enriched in cancer-related pathways. The ESTIMATE and CIBERSORT algorithms revealed that the low-risk group had a higher abundance of anti-tumor immunocyte infiltration (P < 0.05). Results of Submap, IPS, CIC, TMB, and external immunotherapy cohort (iMvigor210) analyses showed that the low-risk group were indicative of better immunotherapy response (P < 0.05). Conclusions: The novel signature offers a promising way to evaluate the prognosis and treatment efficacy in BC patients, which may facilitate clinical practice and management.

The relationship between immediate postmastectomy reconstruction modalities and survival benefits in patients with triple negative breast cancer.

INTRODUCTION: Immediate postmastectomy reconstruction for breast cancer has been widely used due to its unique esthetic and psychological effects. However, no other population-based study has investigated the effects of different reconstruction types on the survival in patients with triple negative breast cancer (TNBC). METHODS: We selected patients who met the eligibility criteria from the Surveillance, Epidemiology, and End Results cancer registry (N = 9760). We then assessed the effect of different reconstructive surgical approaches (implant, autologous, implant and autologous combined reconstruction) on the overall survival (OS) and breast cancer-specific survival (BCSS) by using the Kaplan-Meier survival curve and Cox proportional hazard regression analyses. The nomograms were used to predict OS and BCSS. And the competitive risk model was used to assess breast cancer-specific death (BCSD) and non-breast cancer-specific death (NBCSD). RESULTS: Statistical analysis suggested that the three reconstruction methods had better OS and BCSS with lower hazard than mastectomy alone (log-rank test, p < 0.05). Multivariate stratified analysis showed that patients aged 40-60 years had the greatest improvement in OS (Adjusted hazard ratio [AHR], 0.646; 95% Confidence Interval [CI], 0.439-0.950; p = 0.026) with combined reconstruction. BCSS could be improved only by implant reconstruction (AHR, 0.672; 95% CI, 0.514-0.878; p = 0.004). In addition, autologous reconstruction (AHR, 0.570; 95% CI, 0.350-0.929; p = 0.024) and implant reconstruction (AHR, 0.538; 95% CI, 0.339-0.853; p = 0.008) improved OS in patients >60 years of age. The survival prediction model quantified the survival benefits of TNBC patients undergoing different surgeries. Moreover, the C-indexes showed the good predictive ability of the nomograms. CONCLUSIONS: Our results suggest that for TNBC patients, there is a survival benefit of immediate postmastectomy reconstruction compared with mastectomy alone. Among them, implant reconstruction has the most obvious advantage.

Prognostic effect of radiotherapy in breast cancer patients underwent immediate reconstruction after mastectomy.

Introduction: It is still unclear whether radiotherapy affects the long-term survival of breast cancer (BC) patients after immediate breast reconstruction (IBR). This study aims to evaluate the actual prognostic impact of radiotherapy on BC patients undergoing IBR, and to construct survival prediction models to predict the survival benefit of radiotherapy. Methods: Data on eligible BC patients were retrieved from the Surveillance, Epidemiology, and End Results (SEER) database. Competing risk models were used to assess breast cause-specific death (BCSD) and non-breast cancer cause-specific death (NBCSD). Kaplan-Meier curve, Cox risk regression model and forest map were used to evaluate and demonstrate overall survival (OS) and breast cancer-specific survival (BCSS). Survival prediction nomograms were used to predict OS and BCSS probabilities. Results: A total of 22,218 patients were selected, 24.9% received radiotherapy and 75.1% were without radiotherapy. Competing risk models showed that whether BCSD or NBCSD, the cumulative long-term risk of death in the radiotherapy group was higher than that in the non-radiotherapy group. The Kaplan-Meier curve showed that patients with different lymph node metastasis had different radiotherapy benefits. Multivariate stratified analysis showed that radiotherapy after autologous reconstruction was associated with poor BCSS in patients with stage N0, and radiotherapy after autologous reconstruction and combined reconstruction improved OS and BCSS in patients with stage N3. The C-indexes of nomogram (between 0.778 and 0.847) and calibration curves showed the good prediction ability of survival prediction model. Conclusions: Radiotherapy can improve OS and BCSS in N3 stage BC patients undergoing immediate autologous reconstruction after mastectomy. The practical nomograms can be used to predict OS and BCSS of patients with or without radiotherapy, which is helpful for individualized treatment.

Miniaturized spectrometers with a tunable van der Waals junction.

Miniaturized computational spectrometers, which can obtain incident spectra using a combination of device spectral responses and reconstruction algorithms, are essential for on-chip and implantable applications. Highly sensitive spectral measurement using a single detector allows the footprints of such spectrometers to be scaled down while achieving spectral resolution approaching that of benchtop systems. We report a high-performance computational spectrometer based on a single van der Waals junction with an electrically tunable transport-mediated spectral response. We achieve high peak wavelength accuracy (∼0.36 nanometers), high spectral resolution (∼3 nanometers), broad operation bandwidth (from ∼405 to 845 nanometers), and proof-of-concept spectral imaging. Our approach provides a route toward ultraminiaturization and offers unprecedented performance in accuracy, resolution, and operation bandwidth for single-detector computational spectrometers.

Identification of glycogene signature as a tool to predict the clinical outcome and immunotherapy response in breast cancer.

Background: Breast cancer is one of the most important diseases in women around the world. Glycosylation modification correlates with carcinogenesis and roles of glycogenes in the clinical outcome and immune microenvironment of breast cancer are unclear. Methods: A total of 1297 breast cancer and normal cases in the TCGA and GTEx databases were enrolled and the transcriptional and survival information were extracted to identify prognostic glycogenes using Univariate Cox, LASSO regression, Multivariate Cox analyses and Kaplan-Meier method. The immune infiltration pattern was explored by the single sample gene set enrichment method. The HLA and immune checkpoint genes expression were also compared in different risk groups. The expressions of a glycogene MGAT5 as well as its products were validated by immunohistochemistry and western blotting in breast cancer tissues and cells. Results: A 19-glycogene signature was identified to separate breast cancer patients into high- and low-risk groups with distinct overall survival rates (P < 0.001). Compared with the high-risk group, proportion of naive B cells, plasma cells and CD8+ T cells increased in the low-risk group (P < 0.001). Besides, expressions of HLA and checkpoint genes, such as CD274, CTLA4, LAG3 and TIGIT3, were upregulated in low-risk group. Additionally, highly expressed MGAT5 was validated in breast cancer tissues and cells. Downstream glycosylation products of MGAT5 were all increased in breast cancer. Conclusions: We identified a 19-glycogene signature for risk prediction of breast cancer patients. Patients in the low-risk group demonstrated a higher immune infiltration and better immunotherapy response. The validation of MGAT5 protein suggests a probable pathway and target for the development and treatment of breast cancer.

Nomogram Predicts the Role of Primary Tumor Surgery on De Novo Stage-IV Breast Cancer Patients: A SEER-Based Competing Risk Analysis Model.

Objective: The efficacy of primary tumor surgery on survival in female patients with de novo stage IV breast cancer (BC) remains unclear. Our study endeavored to develop comprehensive competing risk nomograms to predict clinical outcomes and guide precision treatment in these patients. Participants and Methods: A total of 12281 patients who had distant metastasis at initial BC diagnosis between 2010 and 2017 in the Surveillance Epidemiology and End Results (SEER) database, were enrolled in this study. First, we assessed the impacts of primary tumor surgery on overall survival (OS) and breast cancer-specific survival (BCSS) using the Kaplan-Meier curves. Then subgroup analyses stratified by different metastatic patterns were performed using Cox and competing risk models (CRM). Based on the filtered independent prognostic parameters by CRM, we established two nomograms to predict the probability of breast cancer-specific death (BCSD) at 1-,2- and 3-year intervals. Furthermore, calibration curves and area under the curves (AUC) were conducted for validation. Results: Kaplan-Meier analysis revealed that surgery was associated with better OS and BCSS (P<0.001). Subgroup analyses demonstrated that in bone-only metastases pattern, relative to breast-conserving surgery (BCS), patients receiving mastectomy had worse prognosis and the poorest survival belonged to non-surgery individuals (BCSS: mastectomy: HR=1.35; 95%CI=1.15-1.60; non-surgery: 2.42; 2.08-2.82; OS: mastectomy: 1.44; 1.23-1.68; non-surgery: 2.40; 2.08-2.78). Additionally, no survival difference was observed between BCS and reconstruction recipients (BCSS: HR=1.10; 95%CI=0.85-1.43; OS: 1.11; 0.86-1.44). Furthermore, patients undergoing BCS possessed similar BCSS with mastectomy recipients as well as reconstruction recipients in viscera metastases pattern, whereas non-surgery individuals had a worse survival (mastectomy: HR=1.04; 95%CI=0.92-1.18; reconstruction: 0.86; 0.69-1.06; non-surgery: 1.83; 1.63-2.05). Two competing risk nomograms of distinct metastatic patterns were established to comprehensively predict the survival of patients. Calibration curves indicated the terrific consistency of the models. Moreover, the AUC values in the training and validation sets were in the range of 0.70-0.80, exhibiting good specificity and sensitivity. Conclusion: The surgery implementation was associated with a lower probability of BCSD in de novo stage-IV BC patients. Our nomograms could offer a relatively accurate and individualized prediction of the cumulative incidence rate of BCSD after primary tumor resection.

Identification of a combined apoptosis and hypoxia gene signature for predicting prognosis and immune infiltration in breast cancer.

BACKGROUND: Breast cancer (BC) is the most common malignant tumor worldwide. Apoptosis and hypoxia are involved in the progression of BC, but reliable biomarkers for these have not been developed. We hope to explore a gene signature that combined apoptosis and hypoxia-related genes (AHGs) to predict BC prognosis and immune infiltration. METHODS: We collected the mRNA expression profiles and clinical data information of BC patients from The Cancer Genome Atlas database. The gene signature based on AHGs was constructed using the univariate Cox regression, least absolute shrinkage and selection operator, and multivariate Cox regression analysis. The associations between risk scores, immune infiltration, and immune checkpoint gene expression were studied using single-sample gene set enrichment analysis. Besides, gene signature and independent clinicopathological characteristics were combined to establish a nomogram. Finally, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) were performed on the potential functions of AHGs. RESULTS: We identified a 16-AHG signature (AGPAT1, BTBD6, EIF4EBP1, ERRFI1, FAM114A1, GRIP1, IRF2, JAK1, MAP2K6, MCTS1, NFKBIA, NFKBIZ, NUP43, PGK1, RCL1, and SGCE) that could independently predict BC prognosis. The median score of the risk model divided the patients into two subgroups. By contrast, patients in the high-risk group had poorer prognosis, less abundance of immune cell infiltration, and expression of immune checkpoint genes. The gene signature and nomogram had good predictive effects on the overall survival of BC patients. GO and KEGG analyses revealed that the differential expression of AHGs may be closely related to tumor immunity. CONCLUSION: We established and verified a 16-AHG BC signature which may help predict prognosis, assess potential immunotherapy benefits, and provide inspiration for future research on the functions and mechanisms of AHGs in BC.

A Novel Glycolysis and Hypoxia Combined Gene Signature Predicts the Prognosis and Affects Immune Infiltration of Patients with Colon Cancer.

PURPOSE: We aimed to characterize the expression patterns of glycolysis and hypoxia genes in colon cancers as well as their value in prognosis and immune microenvironment. METHODS: The expression profiles were acquired from the Cancer Genome Atlas database. Enrichment of hypoxia and glycolysis gene sets in colon cancer was identified by gene set enrichment analysis. Then, a prognostic signature was built up after Cox regression analyses, and overall survival analysis validated the predictive ability. Immune status and infiltration in cancer tissues were explored using the single sample gene set enrichment analysis and CIBERSORT algorithm. A nomogram model integrating clinical variables and the gene signature was established and assessed. RESULTS: Altogether, 378 cancer and 39 control cases were enrolled. Three glycolysis gene sets and two hypoxia gene sets were enriched in colon cancer (P < 0.05). Five independent genes (ENO3, GPC1, P4HA1, SPAG4, and STC2) were significantly correlated with prognosis of colon cancer patients. Patients with higher risks had significantly better prognosis than those with lower risks (P = 0.002 and AUC = 0.750), which was also observed in the elderly, female and stage I-II subgroups (P < 0.05). In high-risk cases, proportion of NK cells resting increased (P < 0.05) while that of dendritic cells activated (P < 0.05), dendritic cells resting (P < 0.01) and monocytes (P < 0.01) decreased. Besides, expressions of 22 checkpoint genes were found abnormal in groups with different risks (P < 0.05). The predictive nomogram presented satisfactory performance with C-index of 0.771 (0.712-0.830). The area under ROC curve was 0.796 and 0.803 for 3- and 5-year survival prediction, respectively. CONCLUSION: A glycolysis and hypoxia combined gene signature was a promising method to evaluate the prognosis and immune infiltration of colon cancer patients, which may provide a new tool for cancer management.

Early-life Deprivation and Health Outcomes in Adulthood: Evidence from Childhood Hunger Episodes of Middle-aged and Elderly Chinese.

This paper examines long-term health consequences of early-life food deprivation across late-life health indicators. Our analysis relies on retrospective data of hunger drawn from CHARLS - a nationally representative survey of residents ages 45 and over in Continental China. The survey accurately measured hunger episodes in childhood. Exposure to hunger early in life is found to increase the probability of being overweight, having difficulty with ADLs/IADLs and depression in old age. The adverse cognitive impacts of hunger are confined to women due to gender disparity in nutrition and educational opportunities. We find gender-specific interaction effect between hunger episodes and sibling sex composition.

Single-nanowire spectrometers.

Spectrometers with ever-smaller footprints are sought after for a wide range of applications in which minimized size and weight are paramount, including emerging in situ characterization techniques. We report on an ultracompact microspectrometer design based on a single compositionally engineered nanowire. This platform is independent of the complex optical components or cavities that tend to constrain further miniaturization of current systems. We show that incident spectra can be computationally reconstructed from the different spectral response functions and measured photocurrents along the length of the nanowire. Our devices are capable of accurate, visible-range monochromatic and broadband light reconstruction, as well as spectral imaging from centimeter-scale focal planes down to lensless, single-cell-scale in situ mapping.