The correlation between systemic inflammatory markers and efficiency for advanced gastric cancer patients treated with ICIs combined with chemotherapy.

Currently lacking research to explore the correlation between inflammatory markers and the efficacy of immune checkpoint inhibitors (ICIs) combined with chemotherapy in the treatment of advanced gastric cancer. This study is a retrospective study and included patients with advanced gastric cancer who receiving ICIs combined with chemotherapy from January 2020 to December 2022. We analysed the relationship between systemic inflammatory markers and the efficacy of ICIs combined chemotherapy and constructed a clinical prediction model. A nomogram was constructed based on the results of the bidirectional stepwise regression model. A total of 197 patients were enrolled in the training group, with a median follow-up period of time 26 months. Kaplan Meier analysis showed that the median OS of patients with low systemic immune-inflammatory index (SII) and low platelet to lymphocyte ratio (PLR) was superior to those with high SII and PLR. Univariate and multivariate Cox regression analysis showed that SII, NLR, PLR, and N stage as independent prognostic factors for OS. Adding SII to the conventional model improved the predictive ability of the 12-month OS. A total of 95 patients were included in the validation group, and external validation of the SII-based nomogram showed favourable predictive performance. Baseline SII, PLR, and N stage may serve as independent predictive factors for survival outcomes in advanced gastric cancer patients undergoing ICIs combined with chemotherapy. The SII-based nomogram can provide intuitive and accurate prognosis prediction of individual patients.

Long-term survival after neoadjuvant therapy for triple-negative breast cancer under different treatment regimens: a systematic review and network meta-analysis.

BACKGROUND: Triple-negative breast cancer (TNBC) is a life-threatening subtype of breast cancer with limited treatment options. Therefore, this network meta-analysis (NMA) aimed to evaluate and compare the effect of various neoadjuvant chemotherapy (NCT) options on the long-term survival of patients with TNBC. METHODS: PubMed, Embase, Medline, Cochrane Library, Web of Science, and major international conference databases were systematically searched for randomized controlled trials (RCTs) on the efficacy of various NCT options in patients with TNBC. Searches were performed from January 2000 to June 2023. Study heterogeneity was assessed using the I2 statistic. Hazard ratios (HRs) and 95% confidence intervals (CIs) were used to evaluate disease-free survival (DFS) and overall survival (OS). Odds ratios (ORs) and 95% CIs were used to evaluate the pathologic complete response (pCR). The primary outcome was DFS. RESULTS: We conducted an NMA of 21 RCTs involving 8873 patients with TNBC. Our study defined the combination of anthracyclines and taxanes as the preferred treatment option. On this basis, the addition of any of the following new drugs is considered a new treatment option: bevacizumab (B), platinum (P), poly-ADP-ribose polymerase inhibitors (PARPi), and immune checkpoint inhibitor (ICI). Based on the surface under the cumulative ranking curve (SUCRA) values, the top three SUCRA area values of DFS were taxanes, anthracycline, and cyclophosphamide (TAC; 89.23%); CT (84.53%); and B (81.06%). The top three SUCRA area values of OS were CT (83.70%), TAC (62.02%), and B-containing regimens (60.06%). The top three SUCRA area values of pCR were B + P-containing regimens (82.7%), ICI + P-containing regimens (80.2%), and ICI-containing regimens (61.8%). CONCLUSIONS: This NMA showed that standard chemotherapy is a good choice with respect to long-term survival. Moreover, B associated with P-containing regimens is likely to be the optimal treatment option for neoadjuvant TNBC in terms of pCR.

Third-line Treatment for Metastatic Triple-negative Breast Cancer: A Systematic Review and Network Meta-analysis.

OBJECTIVE: Metastatic triple-negative breast cancer (mTNBC) is an invasive histologic subtype with a poor prognosis and rapid progression. Currently, there is no standard therapy for the third-line treatment of mTNBC. In this study, we conducted a network meta-analysis to compare regimens and determine treatment outcomes. METHODS: We performed a systematic search of PubMed, EMBASE, the Cochrane Central Register of Controlled Bases, and the minutes of major conferences. Progression-free survival, overall survival, and objective response rate were analyzed through network meta-analysis using the R software (R Core Team). The efficacy of the treatment regimens was compared using hazard ratios, odds ratios, and 95% CIs. RESULTS: We evaluated 15 randomized controlled trials involving 6,010 patients. Compared with the physician's choice treatment, sacituzumab govitecan showed significant advantages in progression-free survival and overall survival, with hazard ratio values of 0.41 (95% CI: 0.32-0.52) and 0.48 (95% CI, 0.39-0.60). In terms of objective response rate, sacituzumab govitecan is the best-performing therapy (odds ratio: 10.82; 95% CI: 5.58-20.97). Adverse events among grades 3 to 5 adverse reactions, the incidence of neutropenia and leukopenia in each regimen was higher, whereas the incidence of fever, headache, hypertension, and rash was lower. CONCLUSION: Compared with the treatment of the physician's choice, sacituzumab govitecan appears more efficacious and is the preferred third-line treatment for mTNBC.

Efficacy and safety of first-line treatment for metastatic triple-negative breast cancer: A network meta-analysis.

Background: Metastatic triple-negative breast cancer (mTNBC) is an aggressive histological subtype with poor prognosis. Several first-line treatments are currently available for mTNBC. This study conducted a network meta-analysis to compare these first-line regimens and to determine the regimen with the best efficacy. Methods: A systematic search of PubMed, EMBASE, the Cochrane Central Register of Controlled Bases, and minutes of major conferences was performed. Progression-free survival (PFS), overall survival (OS), and objective response rate (ORR) were analyzed via network meta-analysis using the R software (R Core Team, Vienna, Austria). The efficacy of the treatment regimens was compared using hazard ratios and 95% confidence intervals. Results: A total of 29 randomized controlled trials involving 4607 patients were analyzed. The ranking was based on the surface under the cumulative ranking curve. Network meta-analysis results showed that cisplatin combined with nab-paclitaxel or paclitaxel was superior to docetaxel plus capecitabine in terms of PFS and ORR. For programmed death-ligand 1 (PD-L1) and breast cancer susceptibility gene (BRCA) mutation-positive tumors, atezolizumab/pembrolizumab combined with nab-paclitaxel and talazoparib was superior to docetaxel plus capecitabine. No significant difference was observed among the treatments in OS. Neutropenia, diarrhea, and fatigue were common serious adverse events. Conclusion: Cisplatin combined with nab-paclitaxel or paclitaxel is the preferred first-line treatment for mTNBC. For PD-L1 and BRCA mutation-positive tumors, atezolizumab/pembrolizumab combined with nab-paclitaxel and talazoparib is an effective treatment option. Neutropenia, diarrhea, and fatigue are frequently occurring serious adverse events.

Incidence of antibody-drug conjugate-related fatigue in patients with breast cancer: A systematic review and meta-analysis.

BACKGROUND: Numerous studies have reported the efficacy of antibody-drug conjugates (ADCs) for treating breast cancer. However, during cytotoxic drug treatment, long-term disabling fatigue is common. Moreover, studies in the relevant literature have indicated that fatigue can significantly increase the incidence of depression and sleep disorders. Therefore, this meta-analysis aims to evaluate the incidence of fatigue in breast cancer survivors treated with ADCs. METHODS: PubMed, EMBASE, Web of Science, and Cochrane Library databases were systematically searched for articles and conference abstracts published before March 16, 2023. Further, two authors independently extracted data from the included studies. The primary outcome of this study was the incidence of all-grade fatigue caused by the use of ADCs in patients with breast cancer. Finally, a random-effects model was used to calculate the incidence and 95% confidence intervals (CIs) of the outcome. RESULTS: Overall, 7963 patients from 31 studies were included in this meta-analysis to assess the incidence of fatigue caused by the use of approved and marketed ADCs in patients with breast cancer. Notably, the incidence of all-grade fatigue during ADC monotherapy was 39.84% (95% CI, 35.09%-44.69%). In subgroup analyses, among ADCs, the incidence of trastuzumab deruxtecan-induced fatigue was the highest, with an all-grade fatigue incidence of 47.05% (95% CI, 42.38%-51.75%). Meanwhile, the incidence of trastuzumab emtansine (T-DM1)-induced all-grade fatigue was 35.17% (95% CI, 28.87%-41.74%), which was the lowest among ADCs. Further, the incidence of all-grade fatigue due to sacituzumab govitecan was 42.82% (95% CI, 34.54%-51.32%), which was higher than that due to T-DM1. Moreover, the incidence of fatigue was higher with T-DM1 combination therapy than with monotherapy. CONCLUSIONS: Clinicians have highlighted the high incidence of ADC-related fatigue and its negative impact on patients' physical and mental health, making fatigue an important research variable. The results of this study will further contribute to a comprehensive understanding of ADCs, which have some clinical importance and are of great benefit to patients with breast cancer.

SBCNet: Scale and Boundary Context Attention Dual-Branch Network for Liver Tumor Segmentation.

Automated segmentation of liver tumors in CT scans is pivotal for diagnosing and treating liver cancer, offering a valuable alternative to labor-intensive manual processes and ensuring the provision of accurate and reliable clinical assessment. However, the inherent variability of liver tumors, coupled with the challenges posed by blurred boundaries in imaging characteristics, presents a substantial obstacle to achieving their precise segmentation. In this paper, we propose a novel dual-branch liver tumor segmentation model, SBCNet, to address these challenges effectively. Specifically, our proposed method introduces a contextual encoding module, which enables a better identification of tumor variability using an advanced multi-scale adaptive kernel. Moreover, a boundary enhancement module is designed for the counterpart branch to enhance the perception of boundaries by incorporating contour learning with the Sobel operator. Finally, we propose a hybrid multi-task loss function, concurrently concerning tumors' scale and boundary features, to foster interaction across different tasks of dual branches, further improving tumor segmentation. Experimental validation on the publicly available LiTS dataset demonstrates the practical efficacy of each module, with SBCNet yielding competitive results compared to other state-of-the-art methods for liver tumor segmentation.

Exploring GZMK as a prognostic marker and predictor of immunotherapy response in breast cancer: unveiling novel insights into treatment outcomes.

BACKGROUND: Granzyme K (GZMK) is a crucial mediator released by immune cells to eliminate tumor cells, playing significant roles in inflammation and tumorigenesis. Despite its importance, the specific role of GZMK in breast cancer and its mechanisms are not well understood. METHODS: We utilized data from the TCGA and GEO databases and employed a range of analytical methods including GO, KEGG, GSEA, ssGSEA, and PPI to investigate the impact of GZMK on breast cancer. In vitro studies, including RT-qPCR, CCK-8 assay, cell cycle experiments, apoptosis assays, Celigo scratch assays, Transwell assays, and immunohistochemical methods, were conducted to validate the effects of GZMK on breast cancer cells. Additionally, Cox regression analysis integrating TCGA and our clinical data was used to develop an overall survival (OS) prediction model. RESULTS: Analysis of clinical pathological features revealed significant correlations between GZMK expression and lymph node staging, differentiation grade, and molecular breast cancer subtypes. High GZMK expression was associated with improved OS, progression-free survival (PFS), and recurrence-free survival (RFS), as confirmed by multifactorial Cox regression analysis. Functional and pathway enrichment analyses of genes positively correlated with GZMK highlighted involvement in lymphocyte differentiation, T cell differentiation, and T cell receptor signaling pathways. A robust association between GZMK expression and T cell presence was noted in the breast cancer tumor microenvironment (TME), with strong correlations with ESTIMATEScore (Cor = 0.743, P < 0.001), ImmuneScore (Cor = 0.802, P < 0.001), and StromalScore (Cor = 0.516, P < 0.001). GZMK also showed significant correlations with immune checkpoint molecules, including CTLA4 (Cor = 0.856, P < 0.001), PD-1 (Cor = 0.82, P < 0.001), PD-L1 (Cor = 0.56, P < 0.001), CD48 (Cor = 0.75, P < 0.001), and CCR7 (Cor = 0.856, P < 0.001). Studies indicated that high GZMK expression enhances patient responsiveness to immunotherapy, with higher levels observed in responsive patients compared to non-responsive ones. In vitro experiments confirmed that GZMK promotes cell proliferation, cell division, apoptosis, cell migration, and invasiveness (P < 0.05). CONCLUSION: Our study provides insights into the differential expression of GZMK in breast cancer and its potential mechanisms in breast cancer pathogenesis. Elevated GZMK expression is associated with improved OS and RFS, suggesting its potential as a prognostic marker for breast cancer survival and as a predictor of the efficacy of immunotherapy.

Incidence of thyroid dysfunction caused by immune checkpoint inhibitors combined with chemotherapy: A systematic review and meta-analysis.

BACKGROUND: The combination of immune checkpoint inhibitors (ICIs) and chemotherapy as a first-line treatment for triple-negative breast cancer (TNBC) has been associated with many adverse reactions. Thyroid dysfunction, the most common adverse reaction of the endocrine system, has also attracted significant attention. This study aimed to analyse the effect of ICIs combined with chemotherapy on thyroid function in patients with TNBC. METHODS: As of November 4, 2023, we searched the PubMed, Web of Science, and Cochrane Library databases for clinical trials of ICIs combined with chemotherapy for the treatment of TNBC. The incidence of hypothyroidism and hyperthyroidism was calculated using a random-effects model. RESULTS: In the final analysis, 3,226 patients from 19 studies were included. The total incidence of all-grade hypothyroidism induced by the combination of ICIs and chemotherapy in treating TNBC (12% (95% confidence intervals(CI): 0.10-0.15)) was higher than that of hyperthyroidism (5% (95% CI: 0.04-0.06)). Pembrolizumab combined with chemotherapy caused the highest incidence of all grades of hypothyroidism for 13% (95% CI: 0.05-0.06). Durvalumab combined with chemotherapy caused the highest incidence of all grades of hyperthyroidism, at 7% (95% CI: 0.03-0.11). ICIs combined with chemotherapy caused a higher incidence of all grades of hypothyroidism in advanced TNBC (15% (95% CI: 0.13-0.17)) than in early stage TNBC (10% (95% CI: 0.07-0.13)). CONCLUSION: In TNBC, the incidence of hypothyroidism caused by the combination of ICIs and chemotherapy was significantly higher than that caused by hyperthyroidism. Pembrolizumab combined with chemotherapy resulted in the highest incidence of hypothyroidism. The incidence of hypothyroidism in patients with advanced TNBC was significantly higher than that in patients with early stage TNBC. In addition, ICIs combined with chemotherapy resulted in 16 out of 3,226 patients experiencing grade ≥ 3 thyroid dysfunction. Although the incidence of severe thyroid dysfunction is low, it requires attention. PROSPERO: CRD42023477933.

Bio-inspired Mechanically Responsive Smart Windows for Visible and Near-Infrared Multiwavelength Spectral Modulation.

Mechanochromic light control technology that can dynamically regulate solar irradiation is recognized as one of the leading candidates for energy-saving windows. However, the lack of spectrally selective modulation ability still hinders its application for different scenarios or individual needs. Here, inspired by the generation of structure color and color change of living organisms, a simple layer-by-layer assembly approach toward large-area fabricating mechanically responsive film for visible and near-infrared multiwavelength spectral modulation smart windows is reported here. The assembled SiO2 nanoparticles and W18O49 nanowires enable the film with an optical modulation rate of up to 42.4% at the wavelength of 550 nm and 18.4% for the near-infrared region, separately, and the typical composite film under 50% stretching shows ≈41.6% modulation rate at the wavelength of 550 nm with NIR modulation rate less than 2.7%. More importantly, the introduction of the multilayer assembly structure not only optimizes the film's optical modulation but also enables the film with high stability during 100 000 stretching cycles. A cooling effect of 21.3 and 6.9 °C for the blackbody and air inside a model house in the real environmental application is achieved. This approach provides theoretical and technical support for the new mechanochromic energy-saving windows.

Association between high body mass index and prognosis of patients with early-stage breast cancer: A systematic review and meta-analysis.

Background: A high body mass index (BMI) can indicate overweight or obesity and is a crucial risk factor for breast cancer survivors. However, the association between high BMI and prognosis in early-stage breast cancer (EBC) remains unclear. We aimed to assess the effects of high BMI on the prognosis of patients with EBC. Methods: The PubMed, Embase, and Cochrane Library databases and proceedings of major oncological conferences related to the effects of BMI on the prognosis of breast cancer were searched up to November 2021. Fixed- and random-effects models were used for meta-analyses. Pooled hazard ratios (HRs) and 95% confidence intervals (CIs) for disease-free survival (DFS) and overall survival (OS) were extracted from the included literature. Results: Twenty retrospective cohort studies with 33,836 patients with EBC were included. Overweight patients had worse DFS (HR: 1.16, 95% CI: 1.05-1.27, P = 0.002) and OS (HR: 1.20; 95% CI: 1.09-1.33, P < 0.001). Obesity also had adverse effects on DFS (HR: 1.17, 95% CI: 1.07-1.29, P = 0.001) and OS (HR: 1.30, 95% CI: 1.17-1.45, P < 0.001). Likewise, patients with high BMI had worse DFS (HR: 1.16, 95% CI: 1.08-1.26, P < 0.001) and OS (HR: 1.25, 95% CI: 1.14-1.39, P < 0.001). In subgroup analyses, overweight had adverse effects on DFS (HR: 1.11, 95% CI: 1.04-1.18, P = 0.001) and OS (HR: 1.18, 95% CI: 1.11-1.26, P < 0.001) in multivariate analyses, whereas the relationship that overweight had negative effects on DFS (HR: 1.21, 95% CI: 0.99-1.48, P = 0.058) and OS (HR: 1.39, 95% CI: 0.92-2.10, P = 0.123) was not statistically significant in univariate analysis. By contrast, obesity had adverse effects on DFS (HR: 1.21, 95% CI: 1.06-1.38, P = 0.004 and HR: 1.14, 95% CI: 1.08-1.22, P < 0.001) and OS (HR: 1.33, 95% CI: 1.15-1.54, P < 0.001 and HR: 1.23, 95% CI: 1.15-1.31, P < 0.001) in univariate and multivariate analyses, respectively. Conclusions: Compared with normal weight, increased body weight (overweight, obesity, and high BMI) led to worse DFS and OS in patients with EBC. Once validated, these results should be considered in the development of prevention programs.