SPARC expression in tumor microenvironment induces partial epithelial-to-mesenchymal transition of esophageal adenocarcinoma cells via cooperating with TGF-ß signaling.

Secreted protein, acidic and rich in cysteine (SPARC) has been characterized as an oncoprotein in esophageal squamous cell carcinoma (ESCC), but its involvement in the pathological development of esophageal adenocarcinoma (ESAD) remains poorly understood. In this study, we aimed to explore the sources of SPARC in the tumor microenvironment (TME) and its functional role in ESAD. Bioinformatic analysis was conducted using data from The Cancer Genome Atlas (TCGA)-esophageal cancer (ESCA) and Genotype-Tissue Expression (GTEx). ESAD tumor cell line OE33 and OE19 cells were used as in vitro cell models. Results showed that SPARC upregulation was associated with unfavorable disease-specific survival (DSS) in ESAD. ESAD tumor cells (OE33 and OE19) had no detectable SPARC protein expression. In contrast, IHC staining in ESAD tumor tissues suggested that peritumoral stromal cells (tumor-associated fibroblasts and macrophages) were the dominant SPARC source in TME. Exogenous SPARC induced partial epithelial-to-mesenchymal transition of ESAD cells, reflected by reduced CDH1 and elevated ZEB1/VIM expression at both mRNA and protein levels. Besides, exogenous SPARC enhanced tumor cell invasion. When TGFBR2 expression was inhibited, the activation of TGF-ß signaling induced by exogenous SPARC was impaired. However, the activating effects were rescued by overexpressing mutant TGFBR2 resistant to the shRNA sequence. Copresence of exogenous SPARC and TGF-ß1 induced higher expression of mesenchymal markers and enhanced the invading capability of ESAD cells than TGF-ß1 alone. In conclusion, this study suggests a potential cross-talk between ESAD tumor stromal cells and cancer cells via a SPARC-TGF-ß1 paracrine network.

Construction of lncRNA-m6A gene-mRNA regulatory network to identify m6A-related lncRNAs associated with the progression of lung adenocarcinoma.

BACKGROUND: We evaluated the prognostic value of m6A-related long noncoding RNAs (lncRNAs) in lung adenocarcinoma (LUAD). METHODS: The expression levels of lncRNAs and mRNAs in LUAD and normal adjacent tissues from The Cancer Genome Atlas dataset were analyzed using the limma package. m6A enzyme-related differentially expressed lncRNAs and mRNAs were identified and used to construct a regulatory network. Survival analysis was performed and the correlation between lncRNAs, m6A regulators, and mRNAs was analyzed; followed by functional enrichment analysis. RESULTS: A comparison of LUAD samples and normal tissues identified numerous differentially expressed lncRNAs and mRNAs, demonstrating that a comprehensive network was established. Two lncRNAs and six mRNAs were selected as prognosis related factors including SH3PXD2A-AS1, MAD2L1, CCNA2, and CDC25C. The pathological stage and recurrence status were identified as independent clinical factors (P < 0.05). The expression levels of these RNAs in the different clinical groups were consistent with those in the different risk groups. The interactions of m6A proteins, two lncRNAs, and six mRNAs were predicted, and functional analysis showed that m6A target mRNAs were involved in the cell cycle, progesterone-mediated oocyte maturation, and oocyte meiosis pathways. CONCLUSIONS: These m6A target lncRNAs and mRNAs may be promising biomarkers for predicting clinical prognosis, and the lncRNA-m6A regulator-mRNA regulatory network could improve our understanding of m6A modification in LUAD progression.

Exploration of Different Hypoxia Patterns and Construction of a Hypoxia-Related Gene Prognostic Index in Colorectal Cancer.

Introduction: Immune checkpoint inhibitor (ICI) therapy has been proven to be a highly efficacious treatment for colorectal adenocarcinoma (COAD). However, it is still unclear how to identify those who might benefit the most from ICI therapy. Hypoxia facilitates the progression of the tumor from different aspects, including proliferation, metabolism, angiogenesis, and migration, and improves resistance to ICI. Therefore, it is essential to conduct a comprehensive understanding of the influences of hypoxia in COAD and identify a biomarker for predicting the benefit of ICI. Methods: An unsupervised consensus clustering algorithm was used to identify distinct hypoxia-related patterns for COAD patients from TCGA and the GEO cohorts. The ssGSEA algorithm was then used to explore the different biological processes, KEGG pathways, and immune characteristics among distinct hypoxia-related clusters. Some hypoxia-related hub genes were then selected by weighted gene coexpression network analysis (WGCNA). Subsequently, univariate Cox regression analysis, multivariate Cox regression analysis, and least absolute shrinkage and selection operator (LASSO) regression were utilized to construct a hypoxia-related gene prognostic index (HRGPI). Finally, validation was also conducted for HRGPI in prognostic value, distinguishing hypoxia-related characteristics and benefits of ICI. Results: We identified four hypoxia-related clusters and found that different hypoxia response patterns induced different prognoses significantly. Again, we found different hypoxia response patterns presented distinct characteristics of biological processes, signaling pathways, and immune features. Severe hypoxia conditions promoted activation of some cancer-related signaling pathways, including Wnt, Notch, ECM-related pathways, and remodeled the tumor microenvironment of COAD, tending to present as an immune-excluded phenotype. Subsequently, we selected nine genes (ANO1, HOXC6, SLC2A4, VIP, CD1A, STC2, OLFM2, ATP6V1B1, HMCN2) to construct our HRGPI, which has shown an excellent prognostic value. Finally, we found that HRGPI has an advantage in distinguishing immune and molecular characteristics of hypoxia response patterns, and it could also be an excellent predictive indicator for clinical response to ICI therapy. Conclusion: Different hypoxia response patterns activate different signaling pathways, presenting distinct biological processes and immune features. HRGPI is an independent prognostic factor for COAD patients, and it could also be used as an excellent predictive indicator for clinical response to ICI therapy.

Clinical Study of 2 Radiotherapy Techniques for Semi-Hepatic Alternating Radiotherapy on Diffuse Liver Metastasis in Patients with Breast Cancer.

Objective: To compare the effects of 2 techniques of semi-hepatic alternating radiotherapy on diffuse hepatic metastasis in patients with breast cancer. Methodology: A total of 68 breast cancer patients with diffuse liver metastasis were randomly divided into Group A (semi-hepatic alternating radiotherapy) and Group B (semi-hepatic sequential radiotherapy). In Group A (semi-hepatic sequential radiotherapy), the liver was divided into the first semi-liver and second semi-liver and alternatively treated with semi-hepatic intensity-modulated radiation therapy (IMRT). The interval between the 2 instances of semi-hepatic radiotherapy was 6 h. The average radiotherapy dose to the semi-livers was both 2 Gy/fraction, once a day, 5 times per week, with a total dose of 30 Gy for 15 days. The total radiation therapy time in Group A was 15 days in Group B (semi-hepatic sequential radiotherapy), the livers were divided into the first semi-liver and second semi-liver and treated with semi-hepatic sequential IMRT, The first semi-liver was first treated in the initial stage of radiation therapy, the average radiotherapy dose to the semi-liver was 2 Gy/fraction, once a day, 5 times per week, with a total dose of 30 Gy for 15 days. The second semi-liver was treated next in the second stage of radiation therapy, the average radiotherapy dose to the semi-liver was 2 Gy/fraction, once a day, 5 times per week, with a total dose of 30 Gy for 15 days. The total radiation therapy time in group B was 30 days. Results: The objective response rate (complete response + partial response) of Group A and Group B were 50.0% and 48.5%, respectively (p = .903). The median survival time after metastasis (median survival of recurrence) of Group A and Group B was 16.7 months and 16.2 months, respectively (p = .411). The cumulative survival rates of 6 months, 1 year, 2 years, and 3 years of Group A and Group B were 90.6% (29 of 32) and 84.8% (28 of 33) (p = .478), 65.6% (21 of 32) and 60.6% (20 of 33) (p = .675), 31.2% (10 of 32) and 27.3% (9 of 33) (p = .725), and 15.6% (5 of 32) and 0 (0 of 33) (p = .018), respectively. The differences between the 2 groups showed no statistical significance in terms of cumulative survival rates in 1 year, 2 years, however, the 3-year survival rate was significantly different. The main toxic reactions were digestive tract reactions, abnormal liver functions, and myelosuppression. The incidence of I to II degree gastrointestinal reactions was 78.13% (25 of 32) in Group A and 72.73% (24 of 33) in Group B (p = .614). The incidence of I to II abnormal liver function was 53.13% (17 of 32) in Group A and 48.48% (16 of 33) in Group B (p = .708). The differences between the 2 groups showed no statistical significance. The incidence of I to II myelosuppression was 59.38% (19 of 32) in Group A and 51.52% (17 of 33) in Group B (p = .524), respectively. The differences between the 2 groups showed no statistical significance in terms of adverse effects. Conclusion: Semi-hepatic alternating IMRT was an effective palliative treatment for diffuse liver metastasis in patients with breast cancer. Semi-hepatic alternating radiotherapy showed a trend of prolonged survival time when compared with semi-hepatic sequential radiotherapy. Compared with the former, the latter showed a trend of lower incidences of side effects without any statistical differences. Moreover, the side effects from the 2 radiotherapy techniques can be controlled through appropriate management, which is worthy of further exploration and applications.

Identification of Hypoxia-Immune-Related Gene Signatures and Construction of a Prognostic Model in Kidney Renal Clear Cell Carcinoma.

Introduction: Kidney renal clear cell carcinoma (KIRC), a kind of malignant disease, is a severe threat to public health. Tracking the information of tumor progression and conducting a related dynamic prognosis model are necessary for KIRC. It is crucial to identify hypoxia-immune-related genes and construct a prognostic model due to immune interaction and the influence of hypoxia in the prognosis of patients with KIRC. Methods: The hypoxia and immune status of KIRC patients were identified by utilizing t-SNE and ImmuCellAI for gene expression data. COX and Lasso regression were used to identify some hypoxia-immune-related signature genes and further construct a prognostic risk model based on these genes. Internal and external validations were also conducted to construct a prognostic model. Finally, some potentially effective drugs were screened by the CMap dataset. Results: We found that high-hypoxia and low-immune status tend to induce poor overall survival (OS). Six genes, including PLAUR, UCN, PABPC1L, SLC16A12, NFE2L3, and KCNAB1, were identified and involved in our hypoxia-immune-related prognostic risk model. Internal verification showed that the area under the curve (AUC) for the constructed models for 1-, 3-, 4-, and 5-year OS were 0.768, 0.754, 0.775, and 0.792, respectively. For the external verification, the AUC for 1-, 3-, 4-, and 5-year OS were 0.768, 0.739, 0.763, and 0.643 respectively. Furthermore, the decision curve analysis findings demonstrated excellent clinical effectiveness. Finally, we found that four drugs (including vorinostat, fludroxycortide, oxolinic acid, and flutamide) might be effective and efficient in alleviating or reversing the status of severe hypoxia and poor infiltration of immune cells. Conclusion: Our constructed prognostic model, based on hypoxia-immune-related genes, has excellent effectiveness and clinical application value. Moreover, some small-molecule drugs are screened to alleviate severe hypoxia and poor infiltration of immune cells.