Effects of Local Treatment in Combination with Systemic Therapy for Advanced Esophageal Cancer: A Systematic Review and Meta-analysis.

Purpose: Initial studies investigating the combination of local and systemic treatments in advanced esophageal cancer (EC) have conflicting conclusions regarding survival benefits. The objective of this systematic review and meta-analysis is to assess the efficacy of the addition of local therapy to systemic treatments in patients with advanced EC. Methods and Materials: A systematic literature search was conducted in the PubMed, EMBASE, and CENTRAL databases. Key eligibility criteria included studies that enrolled patients with histologically confirmed EC or esophagogastric junction cancer with metastasis or recurrence and compared survival benefits between the combined local and systemic treatment group and the systemic treatment alone group. Survival outcomes, represented by hazard ratios (HRs) of progression-free survival (PFS) and overall survival (OS), were pooled using a random effects model. The MINORS score was adopted for quality assessment. Risk of bias was statistically examined by Begg's and Egger's tests. Results: A total of 1 randomized controlled trial (RCT) and 10 qualified retrospective studies including 14,489 patients were identified. Addition of local therapy to systemic treatment significantly improved PFS (HR, 0.52; 95% CI, 0.37-0.73; P < .001) and OS (HR, 0.69; 95% CI, 0.58-0.81; P < .0001) compared with systemic treatment alone. The subgroup analysis revealed that combined local and systemic treatment conferred a significant survival advantage in both patients with oligometastasis (PFS: HR, 0.45; 95% CI, 0.31-0.64; P < .0001; OS: HR, 0.62; 95% CI, 0.48-0.79; P < .0001) and recurrence (OS: HR, 0.55; 95% CI, 0.37-0.81; P = .002). Conclusions: In conclusion, addition of local treatment to systemic therapy can improve survival in patients with advanced EC, particularly in those with oligometastasis or recurrent diseases.

Network analysis of histopathological image features and genomics data improving prognosis performance in clear cell renal cell carcinoma.

INTRODUCTION: Clear cell renal cell carcinoma is the most common type of kidney cancer, but the prediction of prognosis remains a challenge. METHODS: We collected whole-slide histopathological images, corresponding clinical and genetic information from the The Cancer Imaging Archive and The Cancer Genome Atlas databases and randomly divided patients into training (n = 197) and validation (n = 84) cohorts. After feature extraction by CellProfiler, we used 2 different machine learning techniques (Least Absolute Shrinkage and Selector Operation-regularized Cox and Support Vector Machine-Recursive Feature Elimination) and weighted gene co-expression network analysis to select prognosis-related image features and genes, respectively. These features and genes were integrated into a joint model using random forest and used to create a nomogram that combines other predictive indicators. RESULTS: A total of 4 overlapped features were identified, represented by the computed histopathological risk score in the random forest model, and showed predictive value for overall survival (test set: 1-year area under the curves (AUC) = 0.726, 3-year AUC = 0.727, and 5-year AUC = 0.764). The histopathological-genetic risk score (HGRS) integrating the genetic information computed performed better than the model that used image features only (test set: 1-year AUC = 0.682, 3-year AUC = 0.734, and 5-year AUC = 0.78). The nomogram (gender, stage, and HGRS) achieved the highest net benefit according to decision curve analysis compared to HGRS or clinical model. CONCLUSION: This study developed a histopathological-genetic-related nomogram by combining histopathological features and clinical predictors, providing a more comprehensive prognostic assessment for clear cell renal cell carcinoma patients.

Effect of Metakaolin on the Microstructural and Chloride Ion Transport Properties of Concrete in Ocean Wave Splashing Zones.

In order to address the problem of the durability deficiency of concrete in wave splash zones in a harsh marine environment, this paper investigates the effects of coupled carbonation, sulfate, and chloride salts on the strength, capillary water absorption, and ion migration properties of cement concrete incorporated with metakaolin, and characterizes the pore structural changes with the mercury-pressure method and AC impedance technique. The results show that, compared with a single chloride salt environment, the improvement in mortar strength and impermeability with carbonation coupling is almost positively correlated with the calcium content in the specimen, and renders its pore structure more refined and denser. In contrast, the presence of sulfate reduces mortar strength and increases the ion migration coefficient. When the three factors of sulfate, carbonation, and chloride salt were coupled, damage to the strength and pore structure of the specimens was the most significant, but the specimen incorporated with 30% metakaolin had its strength improved compared with the blank group specimen; from the perspective of pore structural parameters and transport coefficient, the microstructure was denser, and the impermeability was significantly improved.

Integrative Analysis of Histopathological Images and Genomic Data in Colon Adenocarcinoma.

BACKGROUND: Colon adenocarcinoma (COAD) is one of the most common malignant tumors in the world. The histopathological features are crucial for the diagnosis, prognosis, and therapy of COAD. METHODS: We downloaded 719 whole-slide histopathological images from TCIA, and 459 corresponding HTSeq-counts mRNA expression and clinical data were obtained from TCGA. Histopathological image features were extracted by CellProfiler. Prognostic image features were selected by the least absolute shrinkage and selection operator (LASSO) and support vector machine (SVM) algorithms. The co-expression gene module correlated with prognostic image features was identified by weighted gene co-expression network analysis (WGCNA). Random forest was employed to construct an integrative prognostic model and calculate the histopathological-genomic prognosis factor (HGPF). RESULTS: There were five prognostic image features and one co-expression gene module involved in the model construction. The time-dependent receiver operating curve showed that the prognostic model had a significant prognostic value. Patients were divided into high-risk group and low-risk group based on the HGPF. Kaplan-Meier analysis indicated that the overall survival of the low-risk group was significantly better than the high-risk group. CONCLUSIONS: These results suggested that the histopathological image features had a certain ability to predict the survival of COAD patients. The integrative prognostic model based on the histopathological images and genomic features could further improve the prognosis prediction in COAD, which may assist the clinical decision in the future.

Stemness Related Genes Revealed by Network Analysis Associated With Tumor Immune Microenvironment and the Clinical Outcome in Lung Adenocarcinoma.

Lung adenocarcinoma (LUAD) is one of the leading fatal malignancy with high morbidity and mortality worldwide. However, due to its complicated mechanism and lack of effective clinical therapeutics, early diagnosis and prognosis are still unsatisfactory. Most of the previous studies focused on cancer stem cells (CSCs), the relationship between cancer stemness (stem-like characteristics) and anti-tumor immunity has not been clearly revealed. Therefore, this study aimed to comprehensively analyze the role of cancer stemness and tumor microenvironment (TME) in LUAD using weighted gene co-expression network analysis (WGCNA). We constructed a gene co-expression network, identified key modules, and hub genes, and further explored the relationship between hub gene expression and cancer immunological characteristics through a variety of algorithms, including Estimation of STromal and Immune cells in MAlignant Tumor tissues using Expression data (ESTIMATE) and Gene Set Enrichment Analysis (GSEA). The hub genes were renamed stemness related genes (SRGs), whose functions were examined at the transcription and protein levels through survival analysis with additional samples, Oncomine database, immunohistochemistry, single cell RNA sequencing (scRNA-seq) and single-sample Gene Set Enrichment Analysis (ssGSEA). Subsequently, Tumor Immune Dysfunction and Exclusion (TIDE) and Connectivity Map (CMap) were implemented for treatment and prognosis analyses. As a result, 15 co-expressed SRGs (CCNA2, CCNB1, CDC20, CDCA5, CDCA8, FEN1, KIF2C, KPNA2, MCM6, NUSAP1, RACGAP1, RRM2, SPAG5, TOP2A, and TPX2) were identified. The overexpression of which was discovered to be associated with reduced immune infiltration in LUAD. It was discovered that there was a general negative correlation between cancer stemness and immunity. The expression of SRGs could probably affect our tumor occurrence, progression, the efficacy of chemotherapy and immunotherapy, and clinical outcomes. In conclusion, the 15 SRGs reported in our study may be used as potential candidate biomarkers for prognostic indicators and therapeutic targets after further validation.

HPV infection related immune infiltration gene associated therapeutic strategy and clinical outcome in HNSCC.

BACKGROUND: Head and neck squamous cell carcinoma (HNSCC) is the sixth most common tumor in human. Research has shown that HPV status HNSCC is a unique prognosis factor, which may due to its immune infiltration landscape. But the underlying mechanism is unclear. METHODS: In this study, we used a combination of several bioinformatics tools, including WCGNA, ssGSEA, CIBERSORT, TIDE,etc., to explore significant genes both related to HPV infection status and immune cell infiltration in HNSCC patients. RESULTS: Combined with several bioinformatics algorithms, eight hub genes were identified, including LTB, CD19, CD3D, SKAP1, KLRB1, CCL19, TBC1D10C and ARHGAP4. In HNSCC population, the hub genes had a stable co-expression, which was related to immune cell infiltration, especially CD8+ T cells, and the infiltrative immune cells were in a dysfunctional status. Samples with high hub genes expression presented with better response to immune check point block (ICB) therapy and sensitivity to bleomycin and methotrexate. CONCLUSIONS: The eight hub genes we found presented with a stable co-expression in immune cell infiltration of HPV + ve HNSCC population. The co-expression of hub genes related to an immune microenvironment featuring an increase in immune cells but high degree of immune dysfunction status. Patients with high hub gene expression had a better response to ICB treatment, bleomycin and methotrexate. The co-expression of hub genes may be related to immune infiltration status in patients. The concrete molecular mechanism of hub genes function demands further exploration.

Tumor Targeted Curcumin Delivery by Folate-Modified MPEG-PCL Self-Assembly Micelles for Colorectal Cancer Therapy.

INTRODUCTION: Curcumin (Cur) is a natural extract of Asian spice Curcumin longa, showing multi-targeting capability and low toxicity in anti-tumor activities. The low bioavailability restricts its application as a therapeutic agent. Folate (FA) receptors are highly expressed in many malignant tumors while low expressed in normal tissue. Herein, we developed a self-assembled FA modified MPEG-PCL micelle to incorporate Cur (FA/Nano-Cur) and applied it for colorectal cancer therapy. METHODS: We prepared FA/Nano-Cur micelles and identified their characteristics. The drug release behavior, pharmacokinetics and in vitro anti-tumor activities of FA/Nano-Cur were studied. Furthermore, the in vivo anti-tumor ability assessment and anti-tumor mechanisms investigation were carried out in murine colorectal cancer model. RESULTS: FA/Nano-Cur micelles had an average particle size of 30.47 nm. Elongated T1/2 and larger AUC were found in FA/Nano-Cur group than that in the Free Cur group. MTT assay and apoptotic study indicated the growth inhibitory effect and pro-apoptotic effect of FA/Nano-Cur were the most significant among all treatments. Moreover, the in vivo study demonstrated that FA/Nano-Cur micelles exhibited a much stronger effect to suppress tumor growth, promote tumor apoptosis and attenuate tumor angiogenesis than Free Cur and Nano-Cur micelles. CONCLUSION: The present study demonstrated FA/Nano-Cur micelles might be a promising therapeutic agent in colorectal cancer treatment with distinctive advantages of improved bioavailability, sustained drug release, tumor-targeted delivery and low toxicity.