Comprehensive analysis of Cuproplasia and immune microenvironment in lung adenocarcinoma.

Background: Trace elements such as copper are essential for human health. Recently the journal Nat Rev Cancer has put forward the concept of Cuproplasia, a way of promoting tumor growth through reliance on copper. We attempted to conduct a comprehensive analysis of Cuproplasia-related genes in lung adenocarcinoma (LUAD) to explore the mechanism of action of Cuproplasia-related genes in LUAD. Method: Transcriptome data and clinical information of LUAD were obtained from TCGA-LUAD and GSE31210, and prognostic models of Cuproplasia-related genes were constructed and verified by regression analysis of GSVA, WGCNA, univariate COX and lasso. The signal pathways affected by Cuproplasia-related genes were analyzed by GO, KEGG and hallmarK pathway enrichment methods. Five immunocell infiltration algorithms and IMVIGOR210 data were used to analyze immune cell content and immunotherapy outcomes in the high-low risk group. Results: In the results of WGCNA, BROWN and TURQUOISE were identified as modules closely related to Cuproplasia score. In the end, lasso regression analysis established a Cuproplasia-related signature (CRS) based on 24 genes, and the prognosis of high-risk populations was worse in TCGA-LUAD and GSE31210 datasets. The enrichment analysis showed that copper proliferation was mainly through chromosome, cell cycle, dna replication, g2m checkpoint and other pathways. Immunoinfiltration analysis showed that there were differences in the content of macrophages among the four algorithms. And IMVIGOR210 found that the lower the score, the more effective the immunotherapy was. Conclusion: The Cuproplasia related gene can be used to predict the prognosis and immunotherapy outcome of LUAD patients, and may exert its effect by affecting chromosome-related pathways and macrophages.

Cancer-associated fibroblasts induce growth and radioresistance of breast cancer cells through paracrine IL-6.

In breast cancer, the most numerous stromal cells are cancer-associated fibroblasts (CAFs), which are associated with disease progression and chemoresistance. However, few studies have explored the function of CAFs in breast cancer cell radiosensitivity. Here, CAF-derived conditioned media was observed to induce breast cancer cell growth and radioresistance. CAFs secrete interleukin 6 (IL-6) which activates signal transducer and activator of transcription 3 (STAT3) signaling pathway, thus promoting the growth and radioresistance of breast cancer cells. Treatment with an inhibitor of STAT3 or an IL-6 neutralizing antibody blocked the growth and radioresistance induced by CAFs. In in vivo mouse models, tocilizumab (an IL-6 receptor monoclonal antibody) abrogated CAF-induced growth and radioresistance. Moreover, in breast cancer, a poor response to radiotherapy was associated with IL-6 and p-STAT3 expression. These results indicated that IL-6 mediates cross-talk between breast cancer cells and CAFs in the tumor microenvironment. Our results identified the IL-6/STAT3 signaling pathway as an important therapeutic target in breast cancer radiotherapy.

Efficacy of sorafenib combined with transcatheter hepatic arterial chemoembolization in treating intermediate-advanced hepatocellular carcinoma.

PURPOSE: To explore the efficacy and safety of sorafenib combined with transcatheter hepatic arterial chemoembolization (TACE) in the treatment of intermediate-advanced hepatocellular carcinoma (HCC). METHODS: A total of 132 intermediate-advanced HCC patients were divided into two groups, namely, control group (n=66, TACE) and Sorafenib group (n=66, TACE combined with sorafenib). Then, the clinical efficacy and incidence rate of adverse reactions were compared s. Besides, the levels of tumor markers and liver function indicators were detected before and after treatment. Additionally, the survival of patients was followed up and recorded. RESULTS: The overall response rate (ORR) and clinical benefit rate (CBR) were significantly higher in Sorafenib group than those in control group. Both Sorafenib group and control group exhibited significantly lowered levels of serum AFP, CEA, CA125 and CA19-9 after treatment compared with those before treatment. In addition, such levels were prominently lower in Sorafenib group than those in control group after treatment. Compared with those before treatment, the levels of total bilirubin (TBil) and alanine aminotransferase (ALT), liver function indexes, significantly rose, while the albumin (Alb) level had no obvious changes in the two groups after treatment. Besides, the liver function indexes displayed no statistically significant differences between the two groups after treatment. Based on the results of follow-up, the median overall survival (OS) and 3-year OS were 16.83 months and 25.8% in Sorafenib group and 12.48 months and 15.2% in control group, respectively. CONCLUSION: Sorafenib combined with TACE achieves better clinical efficacy in the treatment of intermediate-advanced HCC in contrast with TACE alone, which is able to significantly reduce the levels of serum tumor markers and prolong the survival of patients, and results in tolerable adverse reactions.

NUCKS1 Promotes Proliferation, Invasion and Migration of Non-Small Cell Lung Cancer by Upregulating CDK1 Expression.

BACKGROUND: Non-small cell lung cancer (NSCLC) is a predominant type of lung cancer with a high mortality rate. OBJECTIVE: The aim of this study is to investigate the roles of nuclear casein kinase and cyclin-dependent kinase substrate 1 (NUCKS1) in NSCLC and to identify the potential mechanisms. MATERIALS AND METHODS: The expression of NUCKS1 in several NSCLC cells was detected firstly. Then, NUCKS1 was overexpressed or silenced in both A549 and NCI-H460 cells, where cell proliferation, invasion and migration were, respectively, determined, using CCK-8, colony formation assay, transwell and wound healing assays. Cell cycle analysis was performed, and the expression-associated proteins were detected by Western blotting. Subsequently, NCI-H460 cells with NUCKS1 overexpression for the subsequent tumor-bearing experiment. And the NUCKS1 expression in tumor tissues was measured by means of immunohistochemistry and Western blotting. Additionally, the STRING database predicted that Cyclin-Dependent Kinase 1 (CDK1) would bind to NUSK1, which was verified by the co-immunoprecipitation assay. Then, CDK1 was silenced by transfection with short hairpin RNA (shRNA)-CDK-1 or by exposure to CDK1 inhibitor p2767-00. And the biological characteristics of proliferation, invasion and migration were examined. RESULTS: Results indicated that NUCKS1 was overly expressed in NSCLC cells, and its overexpression promoted proliferation, invasion and migration of both A549 and NCI-H460 cells while NUCKS1 knockdown displayed the opposite effects. Moreover, the results of the xenograft experiments revealed that NUCKS1-upregulation promoted the tumor growth. Furthermore, the immunoprecipitation assay verified CDK1's interaction with NUCKS1, and CDK1 knockdown alleviates the impact of NUCKS1 overexpression on NSCLC cell proliferation, invasion and migration. CONCLUSION: Taken together, these findings demonstrated that NUCKS1 promotes proliferation, invasion and migration of NSCLC by upregulating CDK1, providing a novel putative target for the clinical treatment of NSCLC.

Development and interpretation of a pathomics-based model for the prediction of microsatellite instability in Colorectal Cancer.

Microsatellite instability (MSI) has been approved as a pan-cancer biomarker for immune checkpoint blockade (ICB) therapy. However, current MSI identification methods are not available for all patients. We proposed an ensemble multiple instance deep learning model to predict microsatellite status based on histopathology images, and interpreted the pathomics-based model with multi-omics correlation. Methods: Two cohorts of patients were collected, including 429 from The Cancer Genome Atlas (TCGA-COAD) and 785 from an Asian colorectal cancer (CRC) cohort (Asian-CRC). We established the pathomics model, named Ensembled Patch Likelihood Aggregation (EPLA), based on two consecutive stages: patch-level prediction and WSI-level prediction. The initial model was developed and validated in TCGA-COAD, and then generalized in Asian-CRC through transfer learning. The pathological signatures extracted from the model were analyzed with genomic and transcriptomic profiles for model interpretation. Results: The EPLA model achieved an area-under-the-curve (AUC) of 0.8848 (95% CI: 0.8185-0.9512) in the TCGA-COAD test set and an AUC of 0.8504 (95% CI: 0.7591-0.9323) in the external validation set Asian-CRC after transfer learning. Notably, EPLA captured the relationship between pathological phenotype of poor differentiation and MSI (P < 0.001). Furthermore, the five pathological imaging signatures identified from the EPLA model were associated with mutation burden and DNA damage repair related genotype in the genomic profiles, and antitumor immunity activated pathway in the transcriptomic profiles. Conclusions: Our pathomics-based deep learning model can effectively predict MSI from histopathology images and is transferable to a new patient cohort. The interpretability of our model by association with pathological, genomic and transcriptomic phenotypes lays the foundation for prospective clinical trials of the application of this artificial intelligence (AI) platform in ICB therapy.

Radiomics-based nomogram using CT imaging for noninvasive preoperative prediction of early recurrence in patients with hepatocellular carcinoma.

PURPOSE: The aim of this study was to develop and validate a radiomics nomogram based on radiomics features and clinical data for the non-invasive preoperative prediction of early recurrence (≤2 years) in patients with hepatocellular carcinoma (HCC). METHODS: We enrolled 262 HCC patients who underwent preoperative contrast-enhanced computed tomography and curative resection (training cohort, n=214; validation cohort, n=48). We applied propensity score matching (PSM) to eliminate redundancy between clinical characteristics and image features, and the least absolute shrinkage and selection operator (LASSO) was used to prevent overfitting. Next, a radiomics signature, clinical nomogram, and combined clinical-radiomics nomogram were built to predict early recurrence, and we compared the performance and generalization of these models. RESULTS: The radiomics signature stratified patients into low-risk and high-risk, which show significantly difference in recurrence free survival and overall survival (P ≤ 0.01). Multivariable analysis identified dichotomised radiomics signature, alpha fetoprotein, and tumour number and size as key early recurrence indicators, which were incorporated into clinical and radiomics nomograms. The radiomics nomogram showed the highest area under the receiver operating characteristic curve (AUC), with significantly superior predictive performance over the clinical nomogram in the training cohort (0.800 vs 0.716, respectively; P = 0.001) and the validation cohort (0.785 vs 0.654, respectively; P = 0.039). CONCLUSION: The radiomics nomogram is a non-invasive preoperative biomarker for predicting early recurrence in patients with HCC. This model may be of clinical utility for guiding surveillance follow-ups and identifying optimal interventional strategies.

Smoking Exposure and Survival of Patients with Esophagus Cancer: A Systematic Review and Meta-Analysis.

Smoking is a well-known major risk factor in development of esophageal cancer, but few studies have reported the association between smoking status and prognosis of these patients. We conduct the present study to summarize current evidence. A computerized search of the PubMed and EMBASE was performed up to April 30, 2015. Eight studies, containing 4,286 patients, were analyzed. In the grouping analysis, among esophageal squamous-cell carcinoma patients, current and former smokers, compared to those who have never smoked, seemed to have a poorer prognosis (HR = 1.41, 95% CI 1.22-1.64, and HR = 1.35, 95% CI 0.92-1.97, resp.). In the subgroup analysis, adverse effects on current smoker compared with never smoker were also observed in China and the other countries (HR = 1.5, 95% CI 1.18-1.92, and HR = 1.36, 95% CI 1.12-1.65, resp.). In the group that ever smoked, we could not get a similar result. No significantly increased risk was found in esophageal adenocarcinoma patients compared to the squamous-cell histology ones. In the smoking intensity analysis, heavy smoking was associated with poor survival in esophageal squamous-cell carcinoma. Our pooled results supported the existence of harmful effects of smoking on survival after esophagus cancer diagnosis.

Efficacy of adding bevacizumab in the first-line chemotherapy of metastatic colorectal cancer: evidence from seven randomized clinical trials.

Background. Efficacy of adding bevacizumab in first-line chemotherapy of metastatic colorectal cancer (mCRC) has been controversial. The aim of this study is to gather current data to analyze efficacy of adding bevacizumab to the most used combination first-line chemotherapy in mCRC, based on the 2012 meta-analysis reported by Macedo et al. Methods. Medline, EMBASE and Cochrane library, meeting presentations and abstracts were searched. Eligible studies were randomized controlled trials (RCTs) which evaluated first-line chemotherapy with or without bevacizumab in mCRC. The extracting data were included and examined in the meta-analysis according to the type of chemotherapy regimen. Results. Seven trials, totaling 3436 patients, were analyzed. Compared with first-line chemothery alone, the adding of bevacizumab did not show clinical benefit for OS both in first-line therapy and the most used combination chemotherapy (HR = 0.89; 95% CI = 0.78-1.02; P = 0.08; HR = 0.93; 95% CI = 0.83-1.05; P = 0.24). In contrast with OS, the addition of bevacizumab resulted in significant improvement for PFS (HR = 0.68; 95% CI = 0.59-0.78; P < 0.00001). Moreover, it also demonstrated statistical benefit for PFS in the most used combination first-line chemotherapy (HR = 0.84; 95% CI = 0.75-0.94; P = 0.002). And the subgroup analysis indicated only capacitabine-based regimens were beneficial. Conclusions. This meta-analysis shows that the addition of bevacizumab to FOLFOX/FOLFIRI/XELOX regimens might not be beneficial in terms of OS. Benefit has been seen when PFS has been taken into account. In subgroup analysis, benefit adding bevacizumab has been seen when capecitabine-based regimens are used. Further studies are warranted to explore the combination with bevacizumab.