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BackgroundOverexpression of heat shock proteins (HSPs) has been observed in a wide range of human tumors, and there is an increasing evidence demonstrated that HSPs play a key role in tumor progression. Several studies were conducted to explore the clinicopathological characteristics and prognostic value of HSPs in hepatocellular carcinoma (HCC), but the results remain controversial. To address this gap, we conducted a systematic review and meta-analysis.MethodsThe eligible literature was obtained from PubMed, Cochrane library, Web of science, Embase, Chinese National Knowledge Infrastructure and Wan Fang databases. We used the odds ratio (OR) and hazard ratio (HR) as the suitable parameters to assess the clinicopathological features and prognostic value of HSPs in HCC patients.ResultsThe meta-analysis results showed that HSPs expression was associated with overall survival (OS) of HCC patients (HR = 1.61, 95%CI = 1.22-2.13, P=0.001, I2 = 62.7%). In addition, the pooled results suggested that HSPs expression was significantly correlated with tumor differentiation (OR = 1.33, 95%CI = 1.08-1.65, P = 0.907), vascular invasion (OR = 1.31, 95%CI = 1.02-1.69, P = 0.921) and lymphatic metastasis (OR=1.98, 95%CI= 1.70-2.31, P = 0.740). Meanwhile, the subgroup analysis showed a significant correlation between the expression of HSP27 (HR=1.69, 95%CI = 1.24-2.31, P = 0.674) and HSP90α (HR=2.03, 95%CI = 1.73-2.40, P = 0.743) with OS of HCC patients.ConclusionsOur meta-analysis confirms that HSPs expression is closely associated with a worse prognosis in HCC patients, and may be directly involved in tumor differentiation and distant metastasis. In addition, the subgroup analysis results demonstrate that the expression of HSP27 and HSP90α can be served as potential prognostic predictors of HCC.

BackgroundClinical treatment of RAS mutant cancers is challenging because of the complexity of the Ras signaling pathway. SLC7A5 is a newly discovered downstream gene of the Ras signaling pathway, but the regulatory mechanism is unclear. We aimed to explore the molecular mechanism and role in KRAS mutant lung adenocarcinoma progression.MethodsKey gene that regulated SLC7A5 in KRAS mutant lung adenocarcinoma was screened by RNA sequencing and bioinformatics analysis. The effect of this gene on the expression of SLC7A5 was studied by RNAi. The regulatory mechanism between the two genes was investigated by immunofluorescence, CoIP, pulldown and yeast two-hybrid assays. The location of the two genes was determined by inhibiting Ras and the downstream pathways PI3K-AKT and MEK-ERK. By in vivo and in vitro experiments, the effects of the key gene on the biological functions of KRAS mutant lung adenocarcinoma were explored.ResultsWe found a novel gene, ZNF24, which upregulated SLC7A5 protein expression rather than mRNA expression in KRAS mutant lung adenocarcinoma. Endogenous protein interactions occurred between ZNF24 and SLC7A5. Ras inhibition reduced the expression of ZNF24 and SLC7A5. ZNF24 and SLC7A5 are located downstream of the MEK-ERK and PI3K-AKT pathways. In vivo and in vitro functional experiments confirmed that the ZNF24-SLC7A5 signaling axis promoted the proliferation, invasion and migration of KRAS mutant lung adenocarcinoma.ConclusionsZNF24 promoted the growth of KRAS mutant lung adenocarcinoma by upregulating SLC7A5 protein expression, which suggested that ZNF24 is a new biomarker of KRAS mutant tumors and could be a new potential therapeutic target for Ras-driven tumors.

BackgroundTo effectively reduce the irradiated bowel volume so as to reduce intestinal toxicity from pelvic radiotherapy, treatment in the prone position with a full bladder on a belly board is widely used in pelvic radiotherapy for rectal cancer patients. However, the clinical applicable condition of this radiotherapy mode is unclear. The aim of this study was to preliminarily identify patients who were not eligible for this radiotherapy mode by analyzing the effect of abdominal circumference on the irradiated bowel volume.MethodsFrom May 2014 to September 2019, 179 patients with locally advanced rectal cancer were retrospectively reviewed in our center. All patients received pelvic radiotherapy. Weight, height, AC, and body mass index (BMI) were used as the research objects, and the irradiated bowel volume at different dose levels (V10, V20, V30, V40, V50) was selected as the outcome variable. Multivariate linear regression and sensitivity analyses were used to evaluate the correlation between AC and irradiated bowel volume. Generalized additive model (GAM) and piecewise linear regression were used to further analyze the possible nonlinear relationship between them.ResultsAmong the four body size indicators, AC showed a negative linear correlation with the irradiated bowel volume, which was the most significant and stable. In adjuvant radiotherapy patients, we further discovered the threshold effect between AC and irradiated bowel volume, as AC was greater than the inflection point (about 71 cm), irradiated bowel volume decreased rapidly with the increase in AC. t-test showed that in patients with small AC (

Drug resistance often occurs after chemotherapy in esophageal cancer patients, leading to cancer metastasis and recurrence. However, the relationship among cancer cell migration, recurrence and drug resistance in esophageal cancer drug-resistant cells has not been clearly explained. In this study, we constructed paclitaxel (PTX)-resistant esophageal cancer cells to explore the causes of drug resistance and poor prognosis after chemotherapy in esophageal cancer. Colony formation assay was used to evaluate the difference of colony formation between parental cells and drug resistance cells. Microsphere formation assay was used to examine the phenotype of stem cells. Wound healing and Transwell assays were used to detect the migration ability of drug-resistant cells. Western blotting and immunofluorescence assays were used to explore the mechanisms. Finally, we used nude mouse xenograft model to explore the tumor characteristics and the expression of relative proteins to verify our findings in vivo. Our study demonstrated that the cancer cell stemness characteristics exist in drug-resistant esophageal cancer cells, that expressed the biomarkers of stem cells and were prone to epithelial-mesenchymal transition (EMT). Our results suggested that the expression of EMT biomarkers and stemness-related proteins increased in esophageal cancer cells after continuously using chemotherapeutic drugs for a period of time. This study indicated that simultaneously targeting EMT and stemness could be a better strategy for the treatment of esophageal cancer drug resistance.

BackgroundBreast cancer (BC) is the most common cancer in women and is highly heterogeneous. BC can be classified into four molecular subtypes based on the status of estrogen receptor (ER), progesterone receptor (PR), human epidermal growth factor receptor 2 (HER2) and proliferation marker protein Ki-67. However, they can only be obtained by biopsy or surgery, which is invasive. Radiomics can noninvasively predict molecular expression via extracting the image features. Nevertheless, there is a scarcity of data available regarding the prediction of molecular biomarker expression using ultrasound (US) images in BC.ObjectivesTo investigate the prediction performance of US radiomics for the assessment of molecular profiling in BC.MethodsA total of 342 patients with BC who underwent preoperative US examination between January 2013 and December 2021 were retrospectively included. They were confirmed by pathology and molecular subtype analysis of ER, PR, HER2 and Ki-67. The radiomics features were extracted and four molecular models were constructed through support vector machine (SVM). Pearson correlation coefficient heatmaps are employed to analyze the relationship between selected features and their predictive power on molecular expression. The receiver operating characteristic curve was used for the prediction performance of US radiomics in the assessment of molecular profiling.Results359 lesions with 129 ER- and 230 ER+, 163 PR- and 196 PR+, 265 HER2- and 94 HER2+, 114 Ki-67- and 245 Ki-67+ expression were included. 1314 features were extracted from each ultrasound image. And there was a significant difference of some specific radiomics features between the molecule positive and negative groups. Multiple features demonstrated significant association with molecular biomarkers. The area under curves (AUCs) were 0.917, 0.835, 0.771, and 0.896 in the training set, while 0.868, 0.811, 0.722, and 0.706 in the validation set to predict ER, PR, HER2, and Ki-67 expression respectively.ConclusionUltrasound-based radiomics provides a promising method for predicting molecular biomarker expression of ER, PR, HER2, and Ki-67 in BC.

BackgroundHypercalcemia induced by multiple myeloma (MM) affects the biological functions of excitable and non-excitable cells. However, red blood cells (RBCs) regulatory effect on calcium in hypercalcemia is still not fully understood.MethodsA total of 113 patients with MM osteolytic lesions were studied retrospectively. Flow cytometry and atomic absorption spectroscopy were used to detect calcium content. Immunofluorescence and Western blotting were used to investigate protein expression. GEO and miRNA databases were used to screen miRNAs. Exosomal miR-4261 migration was investigated by Transwell assay. Dual-luciferase assays confirmed the targeting relationship between miR-4261 and ATP2B4. An RBC oxidative stress model was constructed, and Omega-Agatoxin IVA was used to study the role of plasma membrane Ca2+-ATPase 4 (PMCA4) in RBCs.ResultsThe results showed that MM RBCs had calcium overload, and serum calcium levels increased as the number of RBCs decreased. The expression of PMCA4 in MM RBCs was significantly lower than in normal RBCs. The exosomal miR-4261 produced by MM cells could be transferred to RBCs to downregulate the expression of ATP2B4.ConclusionsStudies have confirmed that RBCs experience calcium overload in MM with osteolytic lesions, which is related to the downregulation of ATP2B4 by MM exosomal miR-4261.

Hepatocellular carcinoma is a disastrous cancer with an aberrant metabolism. In this study, we aimed to assess the role of metabolism in the prognosis of hepatocellular carcinoma. Ten metabolism-related pathways were identified to classify the hepatocellular carcinoma into two clusters: Metabolism_H and Metabolism_L. Compared with Metabolism_L, patients in Metabolism_H had lower survival rates with more mutated TP53 genes and more immune infiltration. Moreover, risk scores for predicting overall survival based on eleven differentially expressed metabolic genes were developed by the least absolute shrinkage and selection operator (LASSO)-Cox regression model in The Cancer Genome Atlas (TCGA) dataset, which was validated in the International Cancer Genome Consortium (ICGC) dataset. The immunohistochemistry staining of liver cancer patient specimens also identified that the 11 genes were associated with the prognosis of liver cancer patients. Multivariate Cox regression analyses indicated that the differentially expressed metabolic gene-based risk score was also an independent prognostic factor for overall survival. Furthermore, the risk score (AUC = 0.767) outperformed other clinical variables in predicting overall survival. Therefore, the metabolism-related survival-predictor model may predict overall survival excellently for HCC patients.

BackgroundConsiderable evidence suggests that the heterogeneity of ovarian cancer (OC) is a major cause of treatment failure. Single-cell RNA sequencing (scRNA-seq) is a powerful tool to analyse the heterogeneity of the tumour at the single-cell level, leading to a better understanding of cell function at the genetic and cellular levels.MethodsOC scRNA-seq data were extracted from the Gene Expression Omnibus (GEO) database and the FindCluster () package used for cell cluster analysis. The GSVA package was used for single-sample gene set enrichment analysis (ssGSEA) analysis to obtain a Hallmark gene set score and bulk RNA-seq data were used to analyse the key genes of OC-associated immune cell subsets. CIBERSORT was used to identify immune scores of cells and the “WGCNA” package for the weighted correlation network analysis (WGCNA). KEGG (Kyoto Encyclopedia of Genes and Genomes) and GO (Gene Ontology) analyses of subtype groups were performed by GSEA. Then, univariate Cox and lasso regression were performed to further establish a signature. Finally, qPCR and immunohistochemistry staining were used to evaluate the expression of signature genes in OC.ResultsTwo scRNA-seq (GSE154600 and GES158937) datasets were integrated to obtain 20 cell clusters. T cells or NK cells (cluster 5, 6, 7, 11), B cells (cluster 16, 19, 20) and myeloid cells (cluster 4, 9, 10) were clustered according to immune cell markers. The ssGSEA revealed that M1- and M2-like myeloid cell-related genes were significantly upregulated in P3 and P4 patients in the GSE154600 data. Immune cell analysis in TCGA-OC showed that a high abundance of M1-like tumour-associated macrophages (TAMS) predicts better survival. WGCNA, univariate Cox and lasso Cox regression established a two-gene signature (RiskScore=-0.059*CXCL13-0.034*IL26). Next, the TCGA-test and TCGA-OC were used to test the risk prediction ability of the signature, showing a good effect in the datasets. Moreover, the qPCR and immunohistochemistry staining revealed that the expression of CXCL13 and IL26 was reduced in OC tissues.ConclusionA two-gene signature prognostic stratification system (CXCL13 and IL26) was developed based on the heterogeneity of OC immune cells to accurately evaluate the prognostic risk.

Hepatocellular carcinoma (HCC) samples were clustered into three energy metabolism-related molecular subtypes (C1, C2, and C3) with different prognosis using the gene expression data from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO). HCC energy metabolism-related molecular subtype analysis was conducted based on the 594 energy metabolism genes. Differential expression analysis yielded 576 differentially expressed genes (DEGs) among the three subtypes, which were closely related to HCC progression. Six genes were finally selected from the 576 DEGs through LASSO-Cox regression and used in constructing a six-gene signature-associated prognostic risk model, which was validated using the TCGA internal and three GEO external validation cohorts. The risk model showed that high ANLN, ENTPD2, TRIP13, PLAC8, and G6PD expression levels were associated with bad prognosis, and high expression of ADH1C was associated with a good prognosis. The validation results showed that our risk model had a high distinguishing ability of prognosis in HCC patients. The four enriched pathways of the risk model were obtained by gene set enrichment analysis (GSEA) and found to be associated with the tumorigenesis and development of HCC, including the cell cycle, Wnt signaling pathway, drug metabolism cytochrome P450, and primary bile acid biosynthesis. The risk score calculated from the established risk model in 204 samples and other clinical characteristics were used in building a nomogram with a good prognostic prediction ability (C-index = 0.746, 95% CI = 0.714–0.777). The area under the curves (AUCs) of the nomogram model in 1-, 2-, and 3-years were 0.82, 0.77, and 0.79, respectively. Then, qRT-PCR and immunohistochemistry were used to validate the mRNA expression levels of the six genes, and significant differences in mRNA and gene expression were observed among the tumor and adjacent tissues. Overall, our study divided HCC patients into three energy metabolism-related molecular subtypes with different prognosis. Then, a risk model with a good performance in prognostic prediction was built using the TCGA dataset. This model can be used as an independent prognostic evaluation index for HCC patients.

In this study, we collected genes related to energy metabolism, used gene expression data from public databases to classify molecular subtypes of colon cancer (COAD) based on the genes related to energy metabolism, and further evaluated the relationships between the molecular subtypes and prognosis and clinical characteristics. Differential expression analysis of the molecular subtypes yielded 1948 differentially expressed genes (DEGs), whose functions were closely related to the occurrence and development of cancer. Based on the DEGs, we constructed a 4-gene prognostic risk model and identified the high expression of FOXD4, ENPEP, HOXC6, and ALOX15B as a risk factor associated with a high risk of developing COAD. The 4-gene signature has strong robustness and a stable predictive performance in datasets from different platforms not only in patients with early COAD but also in all patients with colon cancer. The enriched pathways of the 4-gene signature in the high- and low-risk groups obtained by GSEA were significantly related to the occurrence and development of colon cancer. Moreover, the results of qPCR, immunohistochemistry staining and Western blot assay revealed that FOXD4, ENPEP, HOXC6, and ALOX15B are over expressed in CRC tissues and cells. These results suggesting that the signature could potentially be used as a prognostic marker for clinical diagnosis.

Colorectal cancer (CRC) is the third leading cause of death in the world. However, the key roles of most molecules in CRC remain unclear. This study aimed to identify key modules and hub genes associated with the progression of CRC. The data of the patients with CRC were obtained from the Gene Expression Omnibus (GEO) database and assessed by weighted gene co-expression network analysis (WGCNA), Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses performed in R. by WGCNA, several hub genes that regulate the mechanism of tumorigenesis in CRC were identified, which were associated with clinical traits. Next, we screened hub genes related to the progression of CRC authenticated by The Cancer Genome Atlas (TCGA) and Oncomine databases. Three hub genes (HCLS1, EVI2B, and CD48) were identified, and survival analysis was further performed. Moreover, the results of qPCR and immunohistochemistry staining revealed that HCLS1, EVI2B, and CD48 are tumor suppressor genes. Further, the functional study verified that over-expression of HCLS1, EVI2B, and CD48 can reduce the proliferation, migration, and invasion ability of CRC cells and significantly suppress CRC tumor growth in vivo. In summary, we identified three hub genes that were associated with the progression of CRC that can be applied in treatment.