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Acute kidney injury (AKI) is commonly present in critically ill patients with sepsis. Early prediction of short-term reversibility of AKI is beneficial to risk stratification and clinical treatment decision. The study sought to use machine learning methods to discriminate between transient and persistent sepsis-associated AKI. Septic patients who developed AKI within the first 48 h after ICU admission were identified from the Medical Information Mart for Intensive Care III database. AKI was classified as transient or persistent according to the Acute Disease Quality Initiative workgroup consensus. Five prediction models using logistic regression, random forest, support vector machine, artificial neural network and extreme gradient boosting were constructed, and their performance was evaluated by out-of-sample testing. A simplified risk prediction model was also derived based on logistic regression and features selected by machine learning algorithms. A total of 5984 septic patients with AKI were included, 3805 (63.6%) of whom developed persistent AKI. The artificial neural network and logistic regression models achieved the highest area under the receiver operating characteristic curve (AUC) among the five machine learning models (0.76, 95% confidence interval [CI] 0.74–0.78). The simplified 14-variable model showed adequate discrimination, with the AUC being 0.76 (95% CI 0.73–0.78). At the optimal cutoff of 0.63, the sensitivity and specificity of the simplified model were 63% and 76% respectively. In conclusion, a machine learning-based simplified prediction model including routine clinical variables could be used to differentiate between transient and persistent AKI in critically ill septic patients. An easy-to-use risk calculator can promote its widespread application in daily clinical practice.

This study aims to explore the recurrence rate and overall survival for patients with cervical cancer after the first treatment and the related risk factors. A retrospective cohort study was conducted on cervical cancer patients enrolled in a cancer specialist hospital in Hunan Province, China from January 1992 to December 2005 and followed up until December 2010. Kaplan–Meier survival analysis was used to estimate the cumulative recurrence rate, and Cox proportional hazards model was utilized to identify risk factors associated with prognosis. A total of 4358 patients were enrolled with a median follow-up of 7.4 years (range 5–19 years), and 372 (8.5%) patients had cancer recurrence. The cumulative recurrence rate showed a rapid increase from 3.8% in the first year after discharge to 8.0% in the fifth year, and the recurrence rate remained relatively stable afterward reaching 9.7% and 10.8% in the 10th and the 15th year, respectively. The median time to recurrence was 15.5 months with an IQR of 5.5–40.0 months. The Cox regression showed that miscarriage, clinical stage, and treatment received were significantly associated with cervical cancer recurrence after adjustment for confounders. Patients with recurrence showed a significantly higher risk for mortality than those without recurrence (HR 2.79, 95% CI 2.42–3.22). This study depicted the long-term recurrence rate and survival after recurrence for patients with cervical cancer after the first treatment, and reported time to recurrence and risk factors related to recurrence. These findings may provide important evidence for designing targeted interventions for the treatment of cervical cancer.

Ferroptosis is a novel type of cell death depending on iron and is strongly related to the development of tumors. Hepatocellular carcinoma (HCC) is a malignancy with high incidence. Despite some reports demonstrating the relation between ferroptosis-related genes and HCC, more details have not been excavated. In the present study, we collected and analyzed HCC patients' datasets from the TCGA-LIHC project and ICGC portal, respectively. Through the bioinformatic methods, we screened 126 differentially expressed genes. Then a prognostic model was established with four genes (GPX2, MT3, PRDX1, and SRXN1). PRDX1 is the hub gene of the prognosis model and has a high expression in hepatocellular carcinoma tumor tissue and cell lines. We further found that silencing PRDX1 increased the accumulation of ferrous ions and lipid peroxidation accumulation in HEPG2 cells and promoted ferroptosis in hepatocellular carcinoma. In conclusion, the study demonstrated the four-gene signature can be used to predict HCC prognosis. It also revealed the potential function of the ferroptosis-related gene PRDX1 in HCC, which can be a biomarker of the prediction for HCC outcome.

Osteosarcoma (OS) is the most common type of primary malignant bone tumor. The high-throughput sequencing technology has shown potential abilities to illuminate the pathogenic genes in OS. This study was designed to find a powerful gene signature that can predict clinical outcomes. We selected OS cases with gene expression and survival data in the TARGET-OS dataset and GSE21257 datasets as training cohort and validation cohort, respectively. The univariate Cox regression and Kaplan–Meier analysis were conducted to determine potential prognostic genes from the training cohort. These potential prognostic genes underwent a LASSO regression, which then generated a gene signature. The harvested signature’s predictive ability was further examined by the Kaplan–Meier analysis, Cox analysis, and receiver operating characteristic (ROC curve). More importantly, we listed similar studies in the most recent year and compared theirs with ours. Finally, we performed functional annotation, immune relevant signature correlation identification, and immune infiltrating analysis to better study he functional mechanism of the signature and the immune cells’ roles in the gene signature’s prognosis ability. A seventeen-gene signature (UBE2L3, PLD3, SLC45A4, CLTC, CTNNBIP1, FBXL5, MKL2, SELPLG, C3orf14, WDR53, ZFP90, UHRF2, ARX, CORT, DDX26B, MYC, and SLC16A3) was generated from the LASSO regression. The signature was then confirmed having strong and stable prognostic capacity in all studied cohorts by several statistical methods. We revealed the superiority of our signature after comparing it to our predecessors, and the GO and KEGG annotations uncovered the specifically mechanism of action related to the gene signature. Six immune signatures, including PRF1, CD8A, HAVCR2, LAG3, CD274, and GZMA were identified associating with our signature. The immune-infiltrating analysis recognized the vital roles of T cells CD8 and Mast cells activated, which potentially support the seventeen-gene signature’s prognosis ability. We identified a robust seventeen-gene signature that can accurately predict OS prognosis. We identified potential immunotherapy targets to the gene signature. The T cells CD8 and Mast cells activated were identified linked with the seventeen-gene signature predictive power.

Individuals with mild cognitive impairment (MCI) are clinically heterogeneous, with different risks of progression to Alzheimer’s disease. Regular follow-up and examination may be time-consuming and costly, especially for MRI and PET. Therefore, it is necessary to identify a more precise MRI population. In this study, a two-stage screening frame was proposed for evaluating the predictive utility of additional MRI measurements among high-risk MCI subjects. In the first stage, the K-means cluster was performed for trajectory-template based on two clinical assessments. In the second stage, high-risk individuals were filtered out and imputed into prognosis models with varying strategies. As a result, the ADAS-13 was more sensitive for filtering out high-risk individuals among patients with MCI. The optimal model included a change rate of clinical assessments and three neuroimaging measurements and was significantly associated with a net reclassification improvement (NRI) of 0.246 (95% CI 0.021, 0.848) and integrated discrimination improvement (IDI) of 0.090 (95% CI − 0.062, 0.170). The ADAS-13 longitudinal models had the best discrimination performance (Optimism-corrected concordance index = 0.830), as validated by the bootstrap method. Considering the limited medical and financial resources, our findings recommend follow-up MRI examination 1 year after identification for high-risk individuals, while regular clinical assessments for low-risk individuals.

The secretory carrier-associated membrane proteins (SCAMPs) are associated with the development of multiple human cancers. The role of SCAMPs in acute myeloid leukemia (AML), however, remains to be identified. In the present study, we explored expression patterns and prognostic value of SCAMPs and network analysis of SCAMPs-related signaling pathways in AML using Oncomine, GEPIA, cBioPortal, LinkedOmics, DAVID and Metascape databases. Genetic alteration analysis revealed that the mutation rate of SCAMP genes was below 1% (9/1272) in AML, and there was no significant correlation between SCAMPs gene mutation and AML prognosis. However, the SCAMP2/5 mRNA levels were significantly higher in AML patients than in healthy controls. Moreover, high mRNA expressions of SCAMP2/4/5 were associated with poor overall survival, which might be due to that SCAMP2/4/5 and their co-expressed genes were associated with multiple pathways related to tumorigenesis and progression, including human T-cell leukemia virus 1 infection, acute myeloid leukemia, mTOR and NF-kappa B signaling pathways. These results suggest that SCAMP2/4/5 are potential prognostic markers for AML, and that SCAMP2 and SCAMP5 individually or in combination may be used as diagnostic markers for AML.

Previous literatures have suggested the importance of inflammatory response during lung adenocarcinoma (LUAD) development. This study aimed at exploring the inflammation-related genes and developing a prognostic signature for predicting the prognosis of LUAD. Survival‑associated inflammation-related genes were identified by univariate Cox regression analysis in the dataset of The Cancer Genome Atlas (TCGA). The least absolute shrinkage and selection operator (LASSO) penalized Cox regression model was used to derive a risk signature which is significantly negatively correlated with OS and divide samples into high-, medium- and low-risk group. Univariate and multivariate Cox analyses suggested that the level of risk group was an independent prognostic factor of the overall survival (OS). Time-dependent receiver operating characteristic (ROC) curve indicated the AUC of 1-, 3- and 5-years of the risk signature was 0.715, 0.719, 0.699 respectively. A prognostic nomogram was constructed by integrating risk group and clinical features. The independent dataset GSE30219 of Gene Expression Omnibus (GEO) was used for verification. We further explored the differences among risk groups in Gene set enrichment analysis (GSEA), tumor mutation and tumor microenvironment. Furthermore, Single Sample Gene Set Enrichment Analysis (ssGSEA) and the results of Cell-type Identification By Estimating Relative Subsets Of RNA Transcripts (CIBERSORT) suggested the status of immune cell infiltration was highly associated with risk groups. We demonstrated the prediction effect of CTLA-4 and PD-1/PD-L1 inhibitors in the low-risk group was better than that in the high-risk group using two methods of immune score include immunophenoscore from The Cancer Immunome Atlas (TCIA) and TIDE score from Tumor Immune Dysfunction and Exclusion (TIDE). In addition, partial targeted drugs and chemotherapy drugs for lung cancer had higher drug sensitivity in the high-risk group. Our findings provide a foundation for future research targeting inflammation-related genes to predictive prognosis and some reference significance for the selection of immunotherapy and drug regimen for lung adenocarcinoma.

We aimed to examine whether the efficacy of the risk of poor prognosis in patients with coronary artery disease is jointly affected by total cholesterol and baseline serum albumin in a secondary analysis of previous study. We analyzed the data of 204 patients from October 2014 to October 2017 for newly diagnosed stable CAD. The outcome was major adverse cardiac events (MACE; defined as all cause mortality, non fatal myocardial infarction, and non fatal stroke). The median duration of follow-up was 783 days. Multivariable COX model was performed to revalidate the relationship between the sALB and MACE and interaction tests were conducted to find the effects of total cholesterol on their association. A total of 28 MACE occurred among the 204 participants. The risk of MACE varied by baseline serum albumin and total cholesterol. Specifically, lower serum albumin indicated higher risk of MACE (HR 3.52, 95% CI 1.30–9.54), and a test for interaction between baseline serum albumin and total cholesterol on MACE was significant (P = 0.0005). We suggested that baseline serum albumin and total cholesterol could interactively affect the risk of poor prognosis of patients with coronary artery diseases. Our findings need to be confirmed by further randomized trials.

Melanoma is the most lethal type of skin cancer. Despite the breakthroughs in the clinical treatment of melanoma using tumor immunotherapy, many patients do not benefit from these immunotherapies because of multiple immunosuppressive mechanisms. Therefore, there is an urgent need to determine the mechanisms of tumor-immune system interactions and their molecular determinants to improve cancer immunotherapy. In this study, combined analysis of microarray data and single-cell RNA sequencing data revealed the key interactions between immune cells in the melanoma microenvironment. First, differentially expressed genes (DEGs) between normal and malignant tissues were obtained using GEO2R. The DEGs were then subjected to downstream analyses, including enrichment analysis and protein–protein interaction analysis, indicating that these genes were associated with the immune response of melanoma. Then, the GEPIA and TIMER databases were used to verify the differential expression and prognostic significance of hub genes, and the relationship between the hub genes and immune infiltration. In addition, we combined single cell analysis from GSE123139 to identify immune cell types, and validated the expression of the hub genes in these immune cells. Finally, cell-to-cell communication analysis of the proteins encoded by the hub genes and their interactions was performed using CellChat. We found that the CCL5-CCR1, SELPLG-SELL, CXCL10-CXCR3, and CXCL9-CXCR3 pathways might play important roles in the communication between the immune cells in tumor microenvironment. This discovery may reveal the communication basis of immune cells in the tumor microenvironment and provide a new idea for melanoma immunotherapy.

It is rare and understudied for patients with stage T1 colorectal cancer to have synchronous distant metastasis. This study was to determine the clinicopathological factors associated with distant metastasis and prognosis. T1 colorectal cancer patients diagnosed between 2010 and 2015 were obtained from the SEER database. Logistic regression was applied to determine risk factors related to distant metastasis. Cox-proportional hazard models were used to identify the prognostic factors for patients with distant metastasis. Among 21,321 patients identified, 359 (1.8%) had synchronous distant metastasis and 1807 (8.5%) had lymph node metastasis. Multivariate analysis revealed that younger age, positive serum CEA, larger tumor size, positive tumor deposit, perineural invasion, lymph node metastasis, histology of non-adenocarcinoma and poorer differentiation were significantly associated with the increased risk of synchronous distant metastasis. Older age, female, African American, positive CEA, positive lymph node metastasis, positive tumor deposit, larger tumor size, no chemotherapy, inadequate lymph node harvesting and no metastasectomy were correlated with worse survival in these patients with synchronous distant metastasis. Patients with metastasis to the liver displayed the highest rate of positive CEA. We conclude that T1 colorectal cancer patients with multiple risk factors need thorough examinations to exclude synchronous distant metastasis. Chemotherapy, adequate lymph node cleaning and metastasectomy are associated with improved survival for those patients with distant metastases. Positive serum CEA may be useful in predicting distant metastases in patients at stage T1.

The crosstalk between osteosarcoma (OS) development and abnormally expressed microRNA (miR)-601 is not explored explicitly. Here, we identified the downregulated miR-601 in osteosarcoma (OS) through a comprehensive bioinformatics analysis of GEO Datasets. The results indicated that miR-601 was downregulated in both OS cells and tissues. The OS patients with reduced expression of miR-601 displayed worse prognosis. The results of in vitro and in vivo assay revealed that elevated miR-601 inhibited the proliferative, migratory and invasive capacities in OS cells. Mechanically, miR-601 exerted its function via targeting oncogene protein kinase membrane associated tyrosine/threonine 1 (PKMYT1) at post-transcriptional level. Moreover, miR-601 was attenuated by c-Myb at transcriptional level. Taken together, our studies reveal that miR-601 is a suppressive gene negatively correlated with malignancy of OS.

Acute kidney injury (AKI) is common among hospitalized children and is associated with a poor prognosis. The study sought to develop machine learning-based models for predicting adverse outcomes among hospitalized AKI children. We performed a retrospective study of hospitalized AKI patients aged 1 month to 18 years in the Second Xiangya Hospital of Central South University in China from 2015 to 2020. The primary outcomes included major adverse kidney events within 30 days (MAKE30) (death, new renal replacement therapy, and persistent renal dysfunction) and 90-day adverse outcomes (chronic dialysis and death). The state-of-the-art machine learning algorithm, eXtreme Gradient Boosting (XGBoost), and the traditional logistic regression were used to establish prediction models for MAKE30 and 90-day adverse outcomes. The models’ performance was evaluated by split-set test. A total of 1394 pediatric AKI patients were included in the study. The incidence of MAKE30 and 90-day adverse outcomes was 24.1% and 8.1%, respectively. In the test set, the area under the receiver operating characteristic curve (AUC) of the XGBoost model was 0.810 (95% CI 0.763–0.857) for MAKE30 and 0.851 (95% CI 0.785–0.916) for 90-day adverse outcomes, The AUC of the logistic regression model was 0.786 (95% CI 0.731–0.841) for MAKE30 and 0.759 (95% CI 0.654–0.864) for 90-day adverse outcomes. A web-based risk calculator can facilitate the application of the XGBoost models in daily clinical practice. In conclusion, XGBoost showed good performance in predicting MAKE30 and 90-day adverse outcomes, which provided clinicians with useful tools for prognostic assessment in hospitalized AKI children.

Circulating tumor DNA (ctDNA) in peripheral blood has been used to predict prognosis and therapeutic response for triple-negative breast cancer (TNBC) patients. However, previous approaches typically use large comprehensive panels of genes commonly mutated across all breast cancers. Given the reduction in sequencing costs and decreased turnaround times associated with panel generation, the objective of this study was to assess the use of custom micro-panels for tracking disease and predicting clinical outcomes for patients with TNBC. Paired tumor-normal samples from patients with TNBC were obtained at diagnosis (T0) and whole exome sequencing (WES) was performed to identify somatic variants associated with individual tumors. Custom micro-panels of 4–6 variants were created for each individual enrolled in the study. Peripheral blood was obtained at baseline, during Cycle 1 Day 3, at time of surgery, and in 3–6 month intervals after surgery to assess variant allele fraction (VAF) at different timepoints during disease course. The VAF was compared to clinical outcomes to evaluate the ability of custom micro-panels to predict pathological response, disease-free intervals, and patient relapse. A cohort of 50 individuals were evaluated for up to 48 months post-diagnosis of TNBC. In total, there were 33 patients who did not achieve pathological complete response (pCR) and seven patients developed clinical relapse. For all patients who developed clinical relapse and had peripheral blood obtained ≤ 6 months prior to relapse (n = 4), the custom ctDNA micro-panels identified molecular relapse at an average of 4.3 months prior to clinical relapse. The custom ctDNA panel results were moderately associated with pCR such that during disease monitoring, only 11% of patients with pCR had a molecular relapse, whereas 47% of patients without pCR had a molecular relapse (Chi-Square; p-value = 0.10). In this study, we show that a custom micro-panel of 4–6 markers can be effectively used to predict outcomes and monitor remission for patients with TNBC. These custom micro-panels show high sensitivity for detecting molecular relapse in advance of clinical relapse. The use of these panels could improve patient outcomes through early detection of relapse with preemptive intervention prior to symptom onset.

The main route of metastasis of bladder urothelial carcinoma is through lymph nodes; however, its exact mechanism remains unclear. In this study, we found an association of nucleolar and spindle associated protein 1 (NUSAP1) expression with BUC tissues along with lymph node metastasis and the survival prognosis. A total of 178 pathological specimens following radical bladder cancer resection were obtained. NUSAP1 expression was analyzed by immunohistochemistry. We evaluated the correlation between clinicopathological characteristics and NUSAP1 expression. Logistic regression was used to determine the independent variables that influenced lymph node metastasis. Uni- and multi-factorial Cox regression methods were used to determine the prognostic value of NUSAP1 expression in urothelial carcinoma of the bladder. High expression of NUSAP1 in BUC was not significantly related to the patient’s gender, age, or tumor number (p > 0.05), however was significantly associated with pathological grade, tumor diameter, pathological stage, and lymph node metastasis (p p p = 0.002). In addition, high NUSAP1 expression was an independent prognostic predictor for BUC. In BUC, NUSAP1 showed high expression and was significantly associated with lymph node metastasis, pathological stage, pathological grade, and tumor diameter. NUSAP1 was an independent predictor of lymph node metastasis and prognosis in BUC; higher expression indicated poorer prognosis of BUC patients.

Intrahepatic cholestasis of pregnancy (ICP) is a common liver disease during pregnancy, that has serious complications. This study aimed to compare the blood inflammation and biochemical markers of pregnant women with ICP in Southwest China and analyse their diagnostic value for ICP. A controlled cross-sectional study was conducted, and routine blood and biochemical indicators of 304 diagnosed ICP patients and 363 healthy pregnant women undergoing routine prenatal examination were assessed. The blood inflammatory indicators and biochemical indicators were compared between the ICP groups and normal groups. In this study, the levels of the ALT, AST, GGT, TBIL and DBIL biochemical indicators and the levels of WBC, neutrophils, NLR and PLR inflammatory indicators in the ICP group were significantly higher than those in healthy pregnant women (p p

The current diagnostic technologies for assessing the axillary lymph node metastasis (ALNM) status accurately in breast cancer (BC) remain unsatisfactory. Here, we developed a diagnostic model for evaluating the ALNM status using a combination of mRNAs and the T stage of the primary tumor as a novel biomarker. We collected relevant information on T1–2 BC from public databases. An ALNM prediction model was developed by logistic regression based on the screened signatures and then internally and externally validated. Calibration curves and the area under the curve (AUC) were employed as performance metrics. The prognostic value and tumor immune infiltration of the model were also determined. An optimal diagnostic model was created using a combination of 11 mRNAs and T stage of the primary tumor and showed high discrimination, with AUCs of 0.828 and 0.746 in the training sets. AUCs of 0.671 and 0.783 were achieved in the internal validation cohorts. The mean external AUC value was 0.686 and ranged between 0.644 and 0.742. Moreover, the new model has good specificity in T1 and hormone receptor-negative/human epidermal growth factor receptor 2- negative (HR−/HER2−) BC and good sensitivity in T2 BC. In addition, the risk of ALNM and 11 mRNAs were correlated with the infiltration of M2 macrophages, as well as the prognosis of BC. This novel prediction model is a useful tool to identify the risk of ALNM in T1–2 BC patients, particularly given that it can be used to adjust surgical options in the future.

Studies have found that circRNA in exosomes is associated with oral squamous cell carcinoma (OSCC) progression. In this study, we examined the expression of circ_0000199 in circulating exosomes from patients with OSCC and its role in the evaluation of relapse and prognosis. Real‐time quantitative reverse transcription–polymerase chain reaction was performed to assess circ_0000199 expression in circulating exosomes from 108 patients with OSCC and 50 healthy people. Gain- and loss-functional experiments were performed to assess the role of circ_0000199 on cell proliferation and apoptosis in OSCC cells. Our results showed that the high level of circ_0000199 in circulating exosomes was significantly associated with betel quid chewing, tumor size, lymphatic metastasis, and TNM stage in patients with OSCC. In addition, the patients with high exosomal circ_0000199 had higher tumor recurrence rate and higher mortality rate than the patients with low exosomal circ_0000199. Overexpression of circ_0000199 promoted, while knockdown of circ_0000199 inhibited OSCC cell growth. Bioinformatics analysis predicted that circ_0000199 interacted with miR-145-5p and miR-29b-3p simultaneously, which were involved in multiple tumor‐related signaling pathways. In conclusion, upregulation of circ_0000199 in circulating exosomes from patients with OSCC is positively associated with poor survival outcome. Circulating exosomal circ_0000199 can be used as a biomarker and potential therapeutic target for OSCC.

Robotic rectal cancer resection with natural orifice extraction is a recently developed minimally invasive surgery used in the treatment of patients with rectal cancer. However, its safety and feasibility remain undiscussed and controversial. This study reported the clinical outcomes and prognostic factors pertaining to traditional robotic assisted rectal cancer resection alone against that of robotic rectal cancer resection with natural orifice extraction to provide a discussion on this issue. 49 patients who underwent robotic rectal cancer resection with natural orifice extraction and 49 matched patients who underwent conventional robotic assisted rectal cancer resection were systematically analyzed in this study. Regarding the baseline characteristics, after matching, no significant differences were observed between the natural orifice specimen extraction (NOSE) group and the robotic assisted rectal cancer resection (RARC) group. Patients in the NOSE group had a reduced visual analog scale (p p = 0.002) and suffered less surgical stress than those in the RARC group. Moreover, 4 complications were observed in the NOSE group and 7 complications in the RARC group with no significant difference (p = 0.337) in terms of complications. The two groups had a similar survival outcomes, where the 3-year overall survival (p = 0.738) and 3-year progression-free survival (p = 0.986) were all comparable between the two groups. Histological differentiation and T stage could be regarded as independent prognostic factors for 3-year overall survival and 3-year progression-free survival. Robotic rectal cancer resection with natural orifice extraction is a safe and feasible minimally invasive surgery for patients suffering from rectal cancer as it encompasses considerable several advantages. Histological differentiation and T stage may serve as independent prognostic factors for 3-year overall survival and 3-year progression-free survival.

We aimed to reveal clinicopathological features and explore survival-related factors of colorectal signet ring cell carcinoma (SRCC). A population-based study was carried out to investigate colorectal SRCC by using data extracted from the surveillance, epidemiology and end results (SEER) database between 2004 and 2015. In total, 3,278 patients with colorectal SRCC were identified, with a median age of 63 (12–103) years old. The lesions of most patients (60.49%) were located in the cecum–transverse colon. In addition, 81.27% patients had advanced clinical stage (stage III/IV), and 76.69% patients had high pathological grade. The 3–, 5–year cancer‐specific survival and overall survival rate was 35.76%, 29.32% and 32.32%, 25.14%. Multivariate analysis revealed that primary site in cecum–transverse colon, married, received surgery, lymph node dissections ≥ 4 regional lymph nodes were independent favorable prognostic. Meanwhile, aged ≥ 65 years, higher grade, tumor size ˃5 cm and advanced AJCC stage were associated with poor prognosis. Patient age, tumor grade, marital status, tumor size, primary tumor location, AJCC stage, surgery and number of dissected lymph node had significant correlation with prognosis of colorectal SRCC.

Long non-coding RNA (lncRNA) is a prognostic biomarker for many types of cancer. Here, we aimed to study the prognostic value of lncRNA in Breast Invasive Carcinoma (BRCA). We downloaded expression profiles from The Cancer Genome Atlas (TCGA) datasets. Subsequently, we screened the differentially expressed genes between normal tissues and tumor tissues. Univariate Cox, LASSO regression, and multivariate Cox regression analysis were used to construct a lncRNA prognostic model. Finally, a nomogram based on the lncRNAs model was developed, and weighted gene co-expression network analysis (WGCNA) was used to predict mRNAs related to the model, and to perform function and pathway enrichment. We constructed a 6-lncRNA prognostic model. Univariate and multivariate Cox regression analysis showed that the 6-lncRNA model could be used as an independent prognostic factor for BRCA patients. We developed a nomogram based on the lncRNAs model and age, and showed good performance in predicting the survival rates of BRCA patients. Also, functional pathway enrichment analysis showed that genes related to the model were enriched in cell cycle-related pathways. Tumor immune infiltration analysis showed that the types of immune cells and their expression levels in the high-risk group were significantly different from those in the low-risk group. In general, the 6-lncRNA prognostic model and nomogram could be used as a practical and reliable prognostic tool for invasive breast cancer.

Acute kidney injury (AKI) correlates with increased health-care costs and poor outcomes in older adults. However, there is no good scoring system to predict mortality within 30-day, 1-year after AKI in older adults. We performed a retrospective analysis screening data of 53,944 hospitalized elderly patients (age > 65 years) from multi-centers in China. 944 patients with AKI (acute kidney disease) were included and followed up for 1 year. Multivariable regression analysis was used for developing scoring models in the test group (a randomly 70% of all the patients). The established models have been verified in the validation group (a randomly 30% of all the patients). Model 1 that consisted of the risk factors for death within 30 days after AKI had accurate discrimination (The area under the receiver operating characteristic curves, AUROC: 0.90 (95% CI 0.875–0.932)) in the test group, and performed well in the validation groups (AUROC: 0.907 (95% CI 0.865–0.949)). The scoring formula of all-cause death within 1 year (model 2) is a seven-variable model including AKI type, solid tumor, renal replacement therapy, acute myocardial infarction, mechanical ventilation, the number of organ failures, and proteinuria. The area under the receiver operating characteristic (AUROC) curves of model 2 was > 0.80 both in the test and validation groups. Our newly established risk models can well predict the risk of all-cause death in older hospitalized AKI patients within 30 days or 1 year.

Nasopharyngeal carcinoma (NPC) is the malignant tumor arising from the nasopharynx epithelium with ethnic and geographical distribution preference. Y-box binding protein-1 (YB1) is the highly expressed DNA/RNA-binding protein with cold shock domain, and enhanced YB1 expression was proved to be associated with many kinds of malignant tumors. There is no systematic study about the regulation of YB1 and cell proliferation, migration, invasion and stress granules (SGs) in NPC, and the relationship between YB1 expression and clinical characteristics and prognosis of NPC patients. We analyzed the mRNA expression of YBX1 in head and neck squamous carcinoma (HNSC) and NPC in databases, investigated the functions of YB1 in cell proliferation, migration and invasion and SGs formation of NPC cells, and detected expression of YB1 protein in a large scale of NPC samples and analyzed their association with clinicopathological features and prognostic significance of NPC patients. YBX1 mRNA was significantly high expression in HNSC and NPC by bioinformatic analysis, and higher expression of YBX1 mRNA indicated poorer prognosis of HNSC patients. Clinically, the expression of YB1 in NPC tissues was significantly higher than these in the control nasopharyngeal epithelial tissues. We further found that the expression of YB1 had an evidently positive relation with advanced clinical stages of patients with NPC. The overall survival rates (OS) were significantly lower for NPC patients with positive expression of YB1. Multivariate analysis confirmed that positive expression of YB1 was the independent poorer prognostic factor for patients with NPC. Moreover, compared with the immortalized nasopharyngeal epithelial cell line (NP69), the basal level of YB1 in NPC cell lines was significantly higher. Knocking down YB1 may inhibit Akt/mTOR pathway in NPC cells. Knocking down YB1 by small interfering RNAs can reduce the ability of proliferation, migration, invasion and SGs formation of NPC cells. The expression of YB1 in NPC cell lines or patients with NPC was significantly higher. The high expression of YB1 protein may act as one valuable independent biomarker to predict poor prognosis for patients with NPC. Knocking down YB1 may release the malignant phenotype of NPC cells.

Heart failure with reduced ejection fraction (HFrEF) constitutes 50% of HF hospitalizations and is characterized by high rates of mortality. To explore the underlying mechanisms of HFrEF etiology and progression, we studied the molecular and cellular differences in four chambers of non-failing (NF, n = 10) and HFrEF (n = 12) human hearts. We identified 333 genes enriched within NF heart subregions and often associated with cardiovascular disease GWAS variants. Expression analysis of HFrEF tissues revealed extensive disease-associated transcriptional and signaling alterations in left atrium (LA) and left ventricle (LV). Common left heart HFrEF pathologies included mitochondrial dysfunction, cardiac hypertrophy and fibrosis. Oxidative stress and cardiac necrosis pathways were prominent within LV, whereas TGF-beta signaling was evident within LA. Cell type composition was estimated by deconvolution and revealed that HFrEF samples had smaller percentage of cardiomyocytes within the left heart, higher representation of fibroblasts within LA and perivascular cells within the left heart relative to NF samples. We identified essential modules associated with HFrEF pathology and linked transcriptome discoveries with human genetics findings. This study contributes to a growing body of knowledge describing chamber-specific transcriptomics and revealed genes and pathways that are associated with heart failure pathophysiology, which may aid in therapeutic target discovery.

Background Burns are one of the most common injuries in daily life for all ages of population. This study was to investigate the epidemiology and outcomes among burn patients in one of the largest burn centers in the southwest of China. Methods The study was performed at the Institute of Burn Research in the first affiliated with the Army Medical University (AMU). A total of 17939 burn patients were included in this retrospective study. Information regarding demographic, burn characteristics, and the burn severity of ABSI were collected, calculated and compared.Results The age ranged from 257 days to 95 years old. Scalding and flame were the two most common causes to burn injuries, comprising of 91.96% in total. Limbs, head/face/neck, and trunk were the most frequently occurred burn sites, with the number and the percent of 12324 (68.70%), 7989 (44.53%), and 7771 (43.32%), respectively. The average total body surface area (TBSA) was 13.64±16.83% (median 8%) with a range of 0.1~100%. A total of 874 (4.9%) patients had TBSA >50%. The presence of a burn with an inhalation injury was confirmed in 543 patients (3.03%). The average LOS was 32.11±65.72 days (median: 17days). Eventually, the retrospective analysis resulted in the development of a framework of burn management continuum used for developing strategies to prevent and manage severe burns.Conclusions The annual number of burn injuries has kept decreasing, which was partially attributed to the increased awareness and education of burn prevention and the improved burn-preventative circumstances. However, the burn severity and the economic burden were still in a high level. And the gender difference and age difference should be considered when making individualized interventions and rehabilitative treatments.

Backgrounds: Angiosarcoma (AS) is a kind of highly aggressive cancer with high occurrence and mortality rates. This study aimed to establish a comprehensive and validated prognostic nomogram with various clinical indicators in patients with AS.Methods: Data of patients with AS diagnosed after surgery between 2010 and 2015 was retrieved from the Surveillance Epidemiology and End Results (SEER) database. Univariate and multivariate Cox proportional hazards regression analysis were performed to identify the independent prognostic factors associated with survival to construct the predictive nomogram of 3- and 5-year overall survival (OS) and cancer-specific survival (CSS) rates. Concordance-index(C-index), calibration plots and receiver operating characteristic (ROC) curves were applied to evaluate the predictive ability of the nomograms. The further decision curve analysis (DCA) was drawn to confirm the clinical usefulness of the nomograms.Results: 323 patients in total with AS were divided into the training group (N =226) and the validation group (N = 97). After the multivariate Cox regression analysis, gender, age, AJCC stage group 7th ed, T, N and M stage 7th ed, histologic grade and primary site were statistically identified as independent factors with OS and CSS (PConclusion: Our study has developed novel and practical nomograms for predicting prognosis in patients with AS contributing to cancer management.

Preoperative prediction of tumor recurrence after radiofrequency ablation (RFA) in patients with early hepatocellular carcinoma (HCC) is helpful for clinical decision-making before treatment. A total of 162 patients with HCC of 3 cm or less who were completely ablated by percutaneous RFA were divided into a derivation cohort (n = 108) and a validation cohort (n = 54). Based on X-Tiles software, Kaplan–Meier curve analysis and COX multivariate analysis to obtain valuable predictive indicators, a clinical scoring system for predicting tumor recurrence was established. In the verall cohort, derivation cohort and validation cohort, we found circulating tumor cells (CTC) > 2/3.2 mL, alpha-fetoprotein (AFP) > 20 ng/mL, and des-γ-carboxyprothrombin (DCP) > 40 mAU/mL, maximum tumor diameter > 20 mm, and the number of multiple tumors (≥ 2) are independent risk factors affecting tumor recurrence. Each independent risk factor was assigned a score of 1 to construct a predictive clinical scoring system, and X-Tiles software was used to divide the clinical score into a low-risk group (0 score–1 score), a medium-risk group (2 scores–3 scores), and a high-risk group (4 scores–5 scores). The cumulative tumor recurrence rates of patients in the low-risk group, middle-risk group, and high-risk group in 1 year, 2 years, and 3 years were 19.4%/27.5%/30.9%, 37.0%/63.2%/79.9% and 68.2%/100%/100%, respectively (Low-risk group vs medium-risk group: P P

Breast cancer (BC) is one of the most dangerous malignant diseases in females. However, the reliable serum biomarkers of BC still need to be explored. Chemerin levels have been found to be associated with different types of cancer. This study aimed to evaluate the role of serum chemerin as a biomarker of BC diagnosis, as well as the correlation between serum chemerin levels and clinicopathological features. The serum from 248 BC patients, 30 breast benign tumor patients, and 103 healthy controls were collected and serum chemerin levels were determined with enzyme-linked immunosorbent assay. We found that serum levels of chemerin in BC patients were higher than those in healthy control individuals (p

Patients with chronic obstructive pulmonary disease (COPD) repeat acute exacerbations (AE). Global Initiative for Chronic Obstructive Lung Disease (GOLD) is only available for patients in stable phase. Currently, there is a lack of assessment and prediction methods for acute exacerbation of chronic obstructive pulmonary disease (AECOPD) patients during hospitalization. To enhance the monitoring and treatment of AECOPD patients, we develop a novel C5.0 decision tree classifier to predict the prognosis of AECOPD hospitalized patients with objective clinical indicators. The medical records of 410 hospitalized AECOPD patients are collected and 28 features including vital signs, medical history, comorbidities and various inflammatory indicators are selected. The overall accuracy of the proposed C5.0 decision tree classifier is 80.3% (65 out of 81 participants) with 95% Confidence Interval (CI):(0.6991, 0.8827) and Kappa 0.6054. In addition, the performance of the model constructed by C5.0 exceeds the C4.5, classification and regression tree (CART) model and the iterative dichotomiser 3 (ID3) model. The C5.0 decision tree classifier helps respiratory physicians to assess the severity of the patient early, thereby guiding the treatment strategy and improving the prognosis of patients.

Buccal mucosa squamous cell carcinoma (BMSCC) is one of major subsites of oral cancer and is associated with a high rate of metastasis and poor prognosis. Heat shock proteins (HSPs) act as potential prognostic biomarkers in many cancer types. However, the role of HSPD1 in oral cancer, especially in BMSCC, is still unknown. Through data analysis with The Cancer Genome Atlas (TCGA), we found the association of HSPD1 gene expression with tumorigenesis and poor prognosis in oral cancer patients. Our cohort study showed that higher HSPD1 protein level was associated with tumorigenesis and poor prognosis in BMSCC patients with lymph node invasion, suggesting that HSPD1 may be involved in tumor metastasis. Moreover, knockdown of HSPD1 induced E-cadherin expression and decreased the migration and invasion of BMSCC cells. In contrast, ectopic expression of HSPD1 diminished E-cadherin expression and promoted the migration/invasion of BMSCC cells. Further, HSPD1 regulated RelA activation to repress E-cadherin expression, enhancing the migration and invasion of BMSCC cells. Furthermore, HSPD1 protein level was inversely correlated with E-cadherin protein level in tumor tissues and co-expression of high HSPD1/low E-cadherin showed a significant association with poor prognosis in BMSCC patients. Taken together, HSPD1 might repress E-cadherin expression and promote metastatic characters of BMSCC cells for poor prognosis of BMSCC patients.

C6orf141 (Chromosome 6 open reading frame 141) is a novel gene, and its role in oral cancer progression remains unclear. C6orf141 expression in oral squamous cell carcinoma (OSCC) and adjacent normal tissues from 428 patients was examined through immunohistochemistry (IHC). Our results revealed that C6orf141 expression was significantly reduced in OSCC compared with adjacent normal tissues. Low C6orf141 expression was significantly associated with a poor American Joint Committee on Cancer pathological stage (P P = 0.002), and pN stage (P = 0.032). Kaplan–Meier curves revealed that low C6orf141 expression was significantly associated with shorter disease-specific survival (DSS) in patients with OSCC (log-rank P = 0.007). Multivariate analysis indicated that low C6orf141 expression was an independent prognostic biomarker for DSS (adjusted hazard ratio = 1.34; 95% confidence interval = 1.10–1.81; P = 0.05). Additionally, ectopic C6orf141 expression could significantly suppress oral cancer cell proliferation, colony formation, and migratory and invasive abilities. Xenograft tumor growth assay revealed that C6orf141 could significantly suppress oral tumor growth in vivo. Our results suggest that C6orf141 plays a novel tumor-suppressive role in oral cancer cell growth and motility. Furthermore, C6orf141 dysfunction could be a potential prognostic biomarker for OSCC and provide new therapeutic strategies in the future.