Translational cancer research最新文献

Background: Patients with hematologic malignancies (HMs) may be immunocompromised after receiving anti-tumor therapy. Those who also have the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) virus infection face many challenges, including a lack of effective antiviral drugs. This study aimed to investigate the clinical features of the SARS-CoV-2 Omicron variant infection in children with HMs, and the effectiveness of Paxlovid.

Methods: A retrospective, non-randomized study was conducted on pediatric patients with HMs infected with the SARS-CoV-2 Omicron variant who had been admitted to the Shanghai Children's Medical Center, Shanghai, China from December 1, 2022 to March 1, 2023. The Paxlovid-treated group (Group P) comprised 21 patients, and the non-Paxlovid-treated group (Group N) comprised 21 patients. The patients' demographic data, clinical features, and therapeutic outcomes were collected. Statistical tests were used to evaluate the effectiveness of the treatment and related factors.

Results: The clinical course of the SARS-CoV-2 Omicron variant infection for most of the children with HMs was non-severe (97.6%), and only one child progressed to severe disease (2.4%). The most common symptoms were fever (66.7%) and cough (52.4%). Compared with the children in Group N, those in Group P had worse clinical characteristics, including those who previously underwent hematopoietic stem cell transplantation (HSCT) or chimeric antigen receptor T (CAR-T) cell treatment (71.4% vs. 28.6%, P=0.005), and those in the myelosuppressive phase (57.1% vs. 4.8%, P<0.001). Most of the children in Group P were treated with more than two types of antibiotics (76.2% vs. 42.9%, P=0.02). The patients treated with Paxlovid within 5 days of diagnosis had a median viral clearance time of 5 days [interquartile range (IQR), 4-8 days], which was significantly shorter than that of the patients who were not treated with Paxlovid (P=0.03). There were no significant differences in the clinical outcomes between the two groups after the propensity score matching (PSM) analyses. Eight patients (19%) had repeat-positive (re-positive) test results. No factor was found to be statistically significant in predicting re-positive test results based on the binary logistic regression analysis.

Conclusions: Administering Paxlovid within 5 days of the diagnosis of the SARS-CoV-2 Omicron variant infection in children may effectively shorten the clearance time of the virus, but there is still the possibility the patients may have re-positive test results.

Background: The incidence of inflammatory bowel disease (IBD) is increasing every year and is characterized by a prolonged course, frequent relapses, difficulty in curing, and a lack of more efficacious therapeutic biomarkers. The aim of this study was to find key core genes as therapeutic biomarkers for IBD.

Methods: GSE75214 in Gene Expression Omnibus (GEO) was used as the experimental set. The genes in the top 25% of standard deviation of all samples in the experimental set were subjected to systematic weighted gene co-expression network analysis (WGCNA) to find candidate genes. Then, least absolute shrinkage and selection operator (LASSO) logistic regression was used to further screen the central genes. Finally, the validity of hub genes was verified on GEO dataset GSE179285 using "BiocManager" R package.

Results: Twelve well-preserved modules were identified in the experimental set using the WGCNA method. Among them, five modules significantly associated with IBD were screened as clinically significant modules, and four candidate genes were screened from these five modules. Then TIMP1, GUCA2B, and HIF1A were screened as hub genes. These hub genes successfully distinguished tumor samples from healthy tissues by artificial neural network algorithm in an independent test set with an area under the working characteristic curve of 0.946 for the subjects.

Conclusions: IBD differentially expressed gene (DEGs) are involved in immunoregulatory processes. TIMP1, GUCA2B, and HIF1A, as core genes of IBD, have the potential to be therapeutic targets for patients with IBD, and our findings may provide a new outlook on the future treatment of IBD.

Background: Bone metastasis (BM) is a common site of metastasis in patients with intrahepatic cholangiocarcinoma (ICC), significantly impacting the quality of life and prognosis of affected individuals. This investigation aimed to assess the risk of BM development in ICC patients and to prognosticate for patients with ICC-associated BM (ICCBM) through the construction of two nomograms.

Methods: We conducted a retrospective analysis of data from 2,651 ICC patients, including 148 cases of BM, documented in the Surveillance, Epidemiology, and End Results (SEER) database spanning 2010 to 2017. Independent predictors for the occurrence of BM in ICC patients were identified via univariate and multivariate logistic regression analyses; simultaneously, independent prognostic indicators for ICCBM patients were ascertained through univariate and multivariate Cox regression analyses. The utility of the nomograms was evaluated through calibration curves, receiver operating characteristic (ROC) curves, decision curve analysis (DCA), and Kaplan-Meier (KM) analysis.

Results: Independent risk factors for BM in ICC included sex, tumor size, lung metastasis, brain metastasis, and intrahepatic metastasis. For ICCBM patients, independent prognostic factors comprised age, chemotherapy, and radiotherapy. The prognostic nomogram exhibited C-indexes of 0.737 [95% confidential interval (CI): 0.682-0.792] for the training cohort and 0.696 (95% CI: 0.623-0.769) for the validation cohort. Calibration curves demonstrated strong concordance between predicted outcomes and observed events. The areas under the curve (AUC) for 3-, 6-, and 12-month cancer-specific survival (CSS) were 0.853, 0.781, and 0.739, respectively, in the training cohort, and 0.794, 0.822, and 0.780 in the validation cohort. DCA illustrated significant net benefits across a broad spectrum of threshold probabilities. KM analysis revealed 1-, 2-, and 3-year CSS rates of 23.91%, 7.55%, and 2.35%, respectively, with a median CSS of 6 months, underscoring the nomograms' capacity to distinctly stratify patients according to survival risk.

Conclusions: The development of these nomograms offers substantial clinical utility in forecasting BM risk among ICC patients and prognosticating for those with ICCBM, thereby facilitating the formulation of more efficacious treatment modalities.

Background: Breast cancer (BRCA) has surpassed lung cancer to become the malignant tumor with the highest incidence in female population. It occurs in malignant cells in breast tissue and is common worldwide. An increasing body of research indicates that M2 macrophages are critical to the occurrence and progression of BRCA. The aim of this work is to build a predictive model of genes related to invasion and migration of M2 macrophages, forecast the prognosis of patients with BRCA, and then evaluate the efficacy of some targeted treatments.

Methods: The Gene Expression Omnibus (GEO; https://www.ncbi.nlm.nih.gov/geo/) database supplied the GSE20685 dataset, whereas the expression profile a clinical details of BRCA patients were obtained from The Cancer Genome Atlas (TCGA; https://portal.gdc.cancer.gov/) database. The genes linked to M2 macrophages and the differentially elevated genes of invasion and migration were found in GSE20685. To explore the prognosis-related invasion and migration M2 macrophage genes, the TCGA-BRCA dataset was merged with Cox regression and least absolute shrinkage and selection operator (LASSO) regression. GSE58812 was utilized for external validation. After calculating each patient's risk score, the prognostic model was examined by analyses of immune infiltration, medication sensitivity, mutation, and enrichment of the risk score.

Results: The risk score had a strong correlation with both several immune cells and popular anti-tumor medications. Additionally, it was discovered that the risk score was a separate prognostic factor for BRCA.

Conclusions: Based on invasion and migration-related M2 macrophage genes, we investigated and validated predictive characteristics in our study that may offer helpful insights into the progression and prognosis of BRCA.

Background: Tumor necrosis factor receptor 2 (TNFR2) is a subtype of the tumor necrosis factor receptors and is known to promote cancer progression by enhancing cancer cell proliferation and inducing immune suppression. More recently, there are reports that TNFR2 expression is related to the prognosis of patients with cancer, including lung, breast, esophageal, colorectal cancer, and lymphoma. In this study, the correlation between the expression of TNFR2 and the prognosis and clinicopathological factors of cancer was systematically evaluated. This study aimed at elucidating the relationship between TNFR2 and prognosis in patients with cancer.

Methods: PubMed, Embase, and Cochrane Library were searched and a meta-analysis was performed to assess the prognostic and clinicopathological values of TNFR2 expression in patients with cancer.

Results: Nine studies with 2,229 patients were included. High expression of TNFR2 was significantly correlated with poor overall survival (OS) [hazard ratio (HR), 1.76; 95% confidence interval (CI): 1.37-2.27; P<0.001] and disease-free survival (DFS) (HR, 2.75; 95% CI: 1.92-3.92; P<0.001). High expression of TNFR2 was also significantly associated with higher tumor grade [odds ratio (OR), 1.58; 95% CI: 1.26-1.98; P<0.001], higher tumor stage (OR, 2.41; 95% CI: 1.62-3.60; P<0.001) and higher clinical stage (OR, 1.80; 95% CI: 1.44-2.23; P<0.001).

Conclusions: High expression of TNFR2 was related to poor prognosis and could be a prognostic factor in patients with cancer.

Background: According to statistics, colon adenocarcinoma (COAD) ranks third in global incidence and second in mortality. The role of N6-methyladenosine (m6A) modification-dependent ferroptosis in tumor development and progression is gaining attention. Therefore, it is meaningful to explore the biological functions mediated by m6A ferroptosis related genes (m6A-Ferr-RGs) in the prognosis and treatment of COAD. This study aimed to explore the regulatory mechanisms and prognostic features of m6A-Ferr-RGs in COAD based on the COAD transcriptome dataset.

Methods: The expression data of Ferr-RGs and the correlated analysis with prognosis related m6A regulators were conducted to obtain candidate m6A-Ferr-RGs. Then, the differentially expressed genes (DEGs) between COAD and normal samples were intersected with candidate m6A-Ferr-RGs to obtain differentially expressed m6A Ferr-RGs (DE-m6A-Ferr-RGs) in COAD. Cox regression analyses were performed to establish risk model and validated in the GSE17538 and GSE41258 datasets. The nomogram was constructed and verified by calibration curves. Moreover, tumor immune dysfunction and exclusion (TIDE) was used to assess immunotherapy response in two risk groups. Finally, the expression of m6A-Ferr-related prognostic genes was validated by quantitative reverse transcription polymerase chain reaction (qRT-PCR).

Results: In total, 6 model genes (HSD17B11, VEGFA, CXCL2, ASNS, FABP4, and GPX2) were obtained to construct the risk model. The nomogram was established based on the independent prognostic factors for predicting survival of COAD. TIDE assessed that the high-risk group suffered from greater immune resistance. Ultimately, the experimental results confirmed that the expression trends of all model genes were consistent among data from public database.

Conclusions: In this study, m6A-Ferr-related prognostic model for COAD was constructed using transcriptome data and clinical data of COAD in public database, which may have potential immunotherapy and chemotherapy guidance implications.

Background: Tetraspanin 1 (TSPAN1) is a newly discovered protein of the tetrameric protein family encoded by the TSPAN1 gene localized in the 1p34 chromosome region. TSPAN1 has been shown to be associated with various malignancies. In this study, we aimed to investigate the prognostic significance of TSPAN1 in breast cancer. Estrogen receptor-positive (ER+) breast cancer is the largest breast cancer subgroup, and ER-targeted therapies have significantly prolonged survival and improved symptoms in advanced breast cancer. TSPAN1 overexpression was found to be associated with a poor prognosis in ER+ breast cancer.

Methods: We analyzed the expression of TSPAN1 in breast cancer tissues and cell lines using western blotting and quantitative reverse transcription polymerase chain reaction (RT-qPCR).

Results: TSPAN1 expression was higher in breast cancer cells as compared with normal breast tissue. There was a significant association between a high TSPAN1 level and a low survival rate. Inhibition of TSPAN1 significantly reduced the proliferation and invasion of BT474 cells both in vitro and in vivo. The downregulation of TSPAN1 in breast cancer cells significantly reduced the levels of p-mitogen-activated protein kinase 1 (MEK1) (S298) and p-extracellular signal-regulating kinase (ERK) 1/2.

Conclusions: TSPAN1 modulates downstream extracellular matrix (ECM) receptor signaling cascades and promotes cellular proliferation and invasion in breast cancer. TSPAN1 inhibition may be a potential new treatment strategy for breast cancer.

Background: Cancer antigen 125 (CA125) and human epididymis protein 4 (HE4) are the most commonly used tumor biomarkers for ovarian cancer (OC) screening and diagnosis. The risk of ovarian malignancy algorithm (ROMA) score uses these markers, as detected by the Roche system, to predict the risk of OC. This study sought to assess the performance of the Mindray system in detecting CA125 and HE4 for ROMA score calculation in clinical settings.

Methods: Consecutive OC patients and patients with benign pelvic masses were screened and enrolled in this study. The CA125 and HE4 levels of these patients were measured using both the Mindray and Roche systems. The ROMA score for each patient was calculated. Diagnostic performance was evaluated using the area under the curve (AUC) of the receiver operating characteristic (ROC) curve.

Results: The HE4 and CA125 levels were significantly higher in the patients with OC than the patients with benign ovarian masses. Both detection systems showed high efficiency in detecting ovarian cancer. For the premenopausal OC patients, the AUC values for the ROMA score, HE4, and CA125 were 0.866, 0.852, and 0.879, respectively, using the Roche system, and 0.911, 0.902, and 0.883, respectively, using the Mindray system. For the postmenopausal OC patients, the AUC values for the ROMA score, HE4, and CA125 were 0.962, 0.920, and 0.953, respectively, using Roche system, and 0.966, 0.924, and 0.959, respectively, using the Mindray system. The correlation analysis showed strong agreement between the two systems. Among the patients who experienced recurrence, we observed a significant increase in both HE4 and CA125 levels compared to baseline using the Mindray system.

Conclusions: The Mindray and Roche systems provide consistent results. The Mindray system can be used to detect HE4 and CA125 for ROMA score calculation.

Background: Circular RNAs (circRNAs) have been found to be linked to cancer progression and metastasis, but there is not much known about their connection to lung adenocarcinoma (LAC). In the previous study reported by our group, has_circ_0002360 was highly expressed in LAC tissues. The goal of this study was to investigate the potential impact of has_circ_0002360 in LAC.

Methods: Bioinformatics software, TargetScan, and miRanda were used to study the interactions of RNAs. Luciferase reporter assays further confirmed their relationship. The relative expression of has_circ_0002360 in 122 patients and four cell lines of the lung were obtained using real-time qualitative polymerase chain reaction (qRT-PCR). The target gene podocalyxin-like (PODXL) expression was confirmed by immunohistochemistry (IHC) in ten pairs of clinical samples. Then, cell counting kit-8 (CCK8), wound healing, and transwell experiments were applied to examine cell growth, migration, and infection-induced cell invasion. LAC cell lines were infected, and the process was monitored by examination of the related epithelial-mesenchymal transition (EMT) proteins.

Results: The resulting data indicated that has_circ_0002360 and PODXL were overexpressed in LAC tissues, whereas miR-762 expression was repressed. The reduction of has_circ_0002360 or upregulation of miR-762 mitigated the proliferation, migration, invasion of LAC cells. Mechanistically, has_circ_0002360 upregulated PODXL expressions by targeting miR-762 to promote LAC progression.

Conclusions: In general, the has_circ_0002360/miR-762/PODXL axis affected the progress of LAC. The results of our study identified has_circ_0002360 as a novel oncogenic RNA in LAC.

Background: More muscle-invasive bladder cancer (MIBC) patients are now eligible for bladder-preserving therapy (BPT), underscoring the need for precision medicine. This study aimed to identify prognostic predictors and construct a predictive model among MIBC patients who undergo BPT.

Methods: Data relating to MIBC patients were obtained from the Surveillance, Epidemiology and End Results (SEER) database from 2004 to 2016. Eleven features were included to establish multiple models. The predictive effectiveness was assessed using receiver operating characteristic (ROC) curves, calibration plots, decision curve analysis (DCA) and clinical impact curve (CIC). SHapley Additive exPlanations (SHAP) were used to explain the impact of features on the predicted targets.

Results: The ROC showed that Catboost and Random Forest (RF) obtained better predictive discrimination in both 3- and 5-year models [test set area under curves (AUC) =0.80 and 0.83, respectively]. Furthermore, Catboost showed better performance in calibration plots, DCA and CIC. SHAP analysis indicated that age, M stage, tumor size, chemotherapy, T stage and gender were the most important features in the model for predicting the 3-year cancer-specific survival (CSS). In contrast, M stage, age, tumor size and gender as well as the N and T stages were the most important features for predicting the 5-year CSS.

Conclusions: The Catboost model exhibits the highest predictive performance and clinical utility, potentially aiding clinicians in making optimal individualized decisions for MIBC patients with BPT.