Survival Curves Of Patients Research Articles

A deep-learning-based clinical risk stratification for overall survival in adolescent and young adult women with breast cancer.

The objective of this study is to construct a novel clinical risk stratification for overall survival (OS) prediction in adolescent and young adult (AYA) women with breast cancer. From the Surveillance, Epidemiology, and End Results (SEER) database, AYA women with primary breast cancer diagnosed from 2010 to 2018 were included in our study. A deep learning algorithm, referred to as DeepSurv, was used to construct a prognostic predictive model based on 19 variables, including demographic and clinical information. Harrell's C-index, the receiver operating characteristic (ROC) curve, and calibration plots were adopted to comprehensively assess the predictive performance of the prognostic predictive model. Then, a novel clinical risk stratification was constructed based on the total risk score derived from the prognostic predictive model. The Kaplan-Meier method was used to plot survival curves for patients with different death risks, using the log-rank test to compared the survival disparities. Decision curve analyses (DCAs) were adopted to evaluate the clinical utility of the prognostic predictive model. Among 14,243 AYA women with breast cancer finally included in this study, 10,213 (71.7%) were White and the median (interquartile range, IQR) age was 36 (32-38) years. The prognostic predictive model based on DeepSurv presented high C-indices in both the training cohort [0.831 (95% CI 0.819-0.843)] and the test cohort [0.791 (95% CI 0.764-0.818)]. Similar results were observed in ROC curves. The excellent agreement between the predicted and actual OS at 3 and 5years were both achieved in the calibration plots. The obvious survival disparities were observed according to the clinical risk stratification based on the total risk score derived from the prognostic predictive model. DCAs also showed that the risk stratification possessed a significant positive net benefit in the practical ranges of threshold probabilities. Lastly, a user-friendly Web-based calculator was generated to visualize the prognostic predictive model. A prognostic predictive model with sufficient prediction accuracy was construct for predicting OS of AYA women with breast cancer. Given its public accessibility and easy-to-use operation, the clinical risk stratification based on the total risk score derived from the prognostic predictive model may help clinicians to make better-individualized management.

M6A-mediated upregulation of LINC01003 regulates cell migration by targeting the CAV1/FAK signaling pathway in glioma

BackgroundLong non-coding RNAs (lncRNAs) play important roles in the progression of glioma. Here, we examined the potential functions of a lncRNA, LINC01003, in glioma and characterized the underlying molecular mechanisms.MethodsThe GEIPA2 and Chinese Glioma Genome Atlas (CCGA) databases were employed to analyze gene expression and the overall survival curve in patients with glioma. The functions of LINC01003 in glioma growth and migration were assessed by loss-of-function experiments in vitro and in vivo. RNA sequencing was used to determine the signaling pathways effected by LINC01003. Bioinformatics analysis and RNA immunoprecipitation (RIP) assays were used to explore the mechanism underlying the N6-methyladenine (m6A) modification-dependent upregulation of LINC01003 in glioma.ResultsLINC01003 expression was upregulated in glioma cell lines and tissues. Higher LINC01003 expression predicted shorter overall survival time in glioma patients. Functionally, LINC01003 knockdown inhibited the cell cycle and cell proliferation and migration in glioma cells. Mechanistically, RNA sequencing revealed that LINC01003 mediated the focal adhesion signaling pathway. Furthermore, LINC01003 upregulation is induced by m6A modification regulated by METTL3.ConclusionThis study characterized LINC01003 as a lncRNA that contributes to tumorigenesis in glioma and demonstrated that the LINC01003-CAV1-FAK axis serves as a potential therapeutic target for glioma.

The distribution pattern of pelvic lymph nodal metastases in cervical cancer

PurposeDepiction of pelvic lymph node metastasis (LNM) sites among patients with cervical cancer facilitates accurate determination of the extent of dissection and radiotherapy regimens.MethodsA retrospective study of 1182 cervical cancer patients who underwent radical hysterectomy and pelvic lymph node dissection between 2008 and 2018 was performed. The number of removed pelvic lymph nodes and metastasis status in different anatomical regions was analyzed. The prognostic difference of patients with lymph node involvement stratified by various factors was analyzed by Kaplan–Meier method.Results The median number of pelvic lymph nodes detected was 22, mainly from obturator (29.54%) and inguinal (21.14%) sites. Metastatic pelvic lymph nodes were found in 192 patients, with obturator accounting for the highest percentage (42.86%). The patients with lymph node involvement in single site had better prognosis that those in multiple sites. The overall- (P = 0.021) (OS) and progression-free (P < 0.001) survival (PFS) curves of patients with inguinal lymph node metastases were worse compared to those with obturator site. There was no difference in the OS and PFS among patients with 2 and more than 2 lymph nodes involvement.ConclusionAn explicit map of LNM in patients with cervical cancer was presented in this study. Obturator lymph nodes tended to be involved. The prognosis of patients with inguinal lymph node involvement was poor in contrast to that with obturator LNM. In patients with inguinal lymph node metastases, clinical staging needs to be reconsidered and extended radiotherapy to the inguinal region needs to be strengthened.

Effect of preoperative pulmonary artery pressure on the prognosis of end-stage heart failure patients after heart transplantation

ObjectiveTo evaluate the effect of preoperative pulmonary artery pressure on perioperative outcome of end-stage heart failure patients undergoing heart transplantation.MethodsRetrospective analysis was undertaken on the clinical data of patients receiving heart transplantation in the Department of Cardiovascular Surgery of our hospital from March 2017 to March 2022. A ROC curve analysis was developed between mean pulmonary artery pressure (mPAP) and postoperative mortality using mPAP as diagnostic criteria. Patients were divided into groups based on this threshold to determine the best mPAP threshold value for predicting postoperative nosocomial mortality, and the differences in preoperative and intraoperative data, postoperative complications, and clinical prognosis of patients in the two groups were compared. Patients were followed up to draw the survival curve of patients in the two groups.ResultsThe study enlisted the participation of 105 patients. ROC curve research revealed that preoperative pulmonary artery pressure was substantially linked with death following heart transplantation, with mPAP = 30.5mmHg being the best threshold. The group with mPAP ≥ 30.5mmHg had a greater incidence of postoperative ECMO support (28.2% vs. 10.6%, P = 0.021) and a higher incidence of in-hospital mortality (15.4% vs. 1.5%, P = 0.019) than the group with mPAP < 30.5mmHg. The postoperative survival rates of 105 patients were 91.3%, 88.7%, 81.6%, and 77.5% at 1, 2, 3, and 4 years, respectively, however, there was no significant difference between the two groups of patients in the postoperative intermediate-far survival rate (P = 0.431).ConclusionsPreoperative pulmonary artery pressure in patients with end-stage heart failure is intimately correlated with perioperative prognosis of heart transplant recipients. The optimal cut-off mPAP value in predicting perioperative prognosis of heart transplant recipients is 30.5mmHg. In the high mPAP group, perioperative ECMO support rate and perioperative mortality rate are high, which do not affect the medium and long-term prognosis of the recipients undergoing heart transplantation.

Screening and biomarker assessment of ferroptosis genes FLT3 and ALOX5 in lung adenocarcinoma

Abstract Objectives Ferroptosis is a unique process of cell death that specifically requires iron. We investigated ferroptosis genes and their function in lung adenocarcinoma (LUAD) patients. Methods Data on the expression levels of genes associated with ferroptosis were collected from the FerrDb and the Cancer Genome Atlas database. Kaplan-Meier Plotter was employed to generate the survival curves of LUAD patients with high vs low expression of ferroptosis genes. The relationship between immune cell infiltration and ferroptosis genes was analyzed via TIMMER. Immunohistochemical staining was employed to quantitatively evaluate gene expression in 43 LUAD patients. Results A total of 89 ferroptosis genes were found to have significant differential expression between LUAD and normal tissues (p&lt;0.05), 23 of which were selected and consistent prognostic trends were observed based on analysis of RNA-Seq and RNA microarray data (p&lt;0.05). These 23 ferroptosis genes were assigned to 10 high-abundance pathways and 18 functional categories. Besides, the expression of ALOX5 and FTL3 demonstrated a positive correlation with sets of immune markers. The expression of ALOX5 exhibited a positive correlation with the levels of infiltration of dendritic cells, macrophages, neutrophils, and CD4+ T cells, while FLT3 expression correlated with the infiltration of B cells, CD4+ T cells, neutrophils, and dendritic cells. Furthermore, ALOX5 was confirmed to be downregulated in lung tumor tissues (p&lt;0.01). Conclusions Our findings show that the ferroptosis genes FLT3 and ALOX5 play prominent roles in immune cell infiltration during LUAD progression and may serve as prognostic biomarkers for LUAD.

Development of a prognostic scoring system for hepatic vena cava Budd-Chiari syndrome with hepatocellular carcinoma

BackgroundHepatocellular carcinoma (HCC) is a serious complication of hepatic vena cava Budd-Chiari syndrome (HVC-BCS) that significantly reduces the survival time of patients. Our study aimed to analyze the prognostic factors influencing the survival of HVC-BCS patients with HCC and to develop a prognostic scoring system. MethodsThe clinical and follow-up data of 64 HVC-BCS patients with HCC who received invasive treatment at the First Affiliated Hospital of Zhengzhou University between January 2015 and December 2019 were retrospectively analyzed. Kaplan-Meier curves and log-rank tests were used to analyze the survival curve of patients and the difference in prognoses between the groups. Univariate and multivariate Cox regression analyses were performed to analyze the influence of biochemical, tumor, and etiological characteristics on the total survival time of patients, and a new prognostic scoring system was developed according to the regression coefficients of the independent predictors in the statistical model. The prediction efficiency was evaluated using the time-dependent receiver operating characteristics curve and concordance index. ResultsMultivariate analysis showed that serum albumin level < 34 g/L [hazard ratio (HR) = 4.207, 95% confidence interval (CI): 1.816-8.932, P = 0.001], maximum tumor diameter > 7 cm (HR = 8.623, 95% CI: 3.771-19.715, P < 0.001), and inferior vena cava stenosis (HR = 3.612, 95% CI: 1.646-7.928, P = 0.001) were independent predictors of survival. A prognostic scoring system was developed according to the above-mentioned independent predictors, and patients were classified into grades A, B, C and D. Significant differences in survival were found among the four groups. ConclusionsThis study successfully developed a prognostic scoring system for HVC-BCS patients with HCC, which is helpful for clinical evaluation of patient prognosis.

Risk factors for the recurrence of cervical cancer using MR-based T1 mapping: A pilot study.

This study aimed to identify risk factors for recurrence in patients with cervical cancer (CC) through quantitative T1 mapping. A cohort of 107 patients histopathologically diagnosed with CC at our institution between May 2018 and April 2021 was categorized into surgical and non-surgical groups. Patients in each group were further divided into recurrence and non-recurrence subgroups depending on whether they showed recurrence or metastasis within 3 years of treatment. The longitudinal relaxation time (native T1) and apparent diffusion coefficient (ADC) value of the tumor were calculated. The differences between native T1 and ADC values of the recurrence and non-recurrence subgroups were analyzed, and receiver operating characteristic (ROC) curves were drawn for parameters with statistical differences. Logistic regression was performed for analysis of significant factors affecting CC recurrence. Recurrence-free survival rates were estimated by Kaplan-Meier analysis and compared using the log-rank test. Thirteen and 10 patients in the surgical and non-surgical groups, respectively, showed recurrence after treatment. There were significant differences in native T1 values between the recurrence and non-recurrence subgroups in the surgical and non-surgical groups (P<0.05); however, there was no difference in ADC values (P>0.05). The areas under the ROC curve of native T1 values for discriminating recurrence of CC after surgical and non-surgical treatment were 0.742 and 0.780, respectively. Logistic regression analysis indicated that native T1 values were risk factors for tumor recurrence in the surgical and non-surgical groups (P=0.004 and 0.040, respectively). Compared with cut-offs, recurrence-free survival curves of patients with higher native T1 values of the two groups were significantly different from those with lower ones (P=0.000 and 0.016, respectively). Quantitative T1 mapping could help identify CC patients with a high risk of recurrence, supplementing information on tumor prognosis other than clinicopathological features and providing the basis for individualized treatment and follow-up schemes.

TP53 Mutations Are Associated with Increased Infections and Reduced Hematopoietic Cell Transplantation Rates in Myelodysplastic Syndrome and Acute Myeloid Leukemia

Although allogeneic hematopoietic cell transplantation (HCT) is the sole potentially curative therapy for patients with poor-risk myelodysplastic syndrome (MDS) and acute myeloid leukemia (AML), only a minority of these patients undergo HCT. Patients with TP53-mutated (TP53MUT) MDS/AML are at particularly high risk, yet fewer TP53MUT patients undergo HCT compared with poor-risk TP53-wild type (TP53WT) patients. We hypothesized that TP53MUT MDS/AML patients have unique risk factors affecting the rate of HCT and thus investigated phenotypic changes that may prevent patients with TP53MUT MDS/AML from receiving HCT. In this single-center retrospective analysis of outcomes for adults with newly diagnosed MDS or AML (n=352), HLA typing was used as a surrogate for physician "intent to transplant." Multivariable logistic regression models were used to estimate odds ratios (ORs) for factors associated with HLA typing, HCT, and pretransplantation infections. Multivariable Cox proportional hazards models were used to create predicted survival curves for patients with and those without TP53 mutations. Overall, significantly fewer TP53MUT patients underwent HCT compared to TP53WT patients (19% versus 31%; P=.028). Development of infection was significantly associated with decreased odds of HCT (OR, .42; 95% CI, .19 to .90) and worse overall survival (hazard ratio, 1.46; 95% CI, 1.09 to 1.96) in multivariable analyses. TP53MUT disease was independently associated with increased odds of developing an infection (OR, 2.18; 95% CI, 1.21 to 3.93), bacterial pneumonia (OR, 1.83; 95% CI, 1.00 to 3.33), and invasive fungal infection (OR, 2.64; 95% CI, 1.34 to 5.22) prior to HCT. Infections were the cause of death in significantly more patients with TP53MUT disease (38% versus 19%; P=.005). With substantially more infections and decreased HCT rates in patients with TP53 mutations, this raises the possibility that phenotypic changes occurring in TP53MUT disease may affect infection susceptibility in this population and drastically impact clinical outcomes.

Abstract P3-05-24: Correlation between the expression of JCAD in plasma exosomes and breast cancer

Abstract Background: Breast cancer is the most common cancer in women. The five-year survival rate of patients with stage 0 and stage I breast cancer is more than 95%, that of patients with stage II breast cancer is 80%, that of patients with stage III breast cancer is about 50%, and that of stage IV breast cancer is less than 30%. The stage of breast cancer is closely related to the prognosis. Exosomes are membrane vesicles secreted by living cells, which carry donor cell specific genetic information. They can exist stably in the circulatory system, so they are ideal biomarkers. Method: We collected 128 breast cancer patients (17 benign cases, 26 stage I cases, 36 stage II cases, 15 stage III cases and 34 stage IV cases) treated in our center from 2018 to 2019. We collected patients’ plasma and extracted exosomes, then we sent them for sequencing. We analyzed the difference between benign cases’ and stage IV cases’ sequencing results, and then we screen them by comprehensively considering the change trend of gene expression from benign cases to stage IV cases, the survival curve of patients and the lymph node metastasis. The clinicopathological factors and progression free survival (PFS) of breast cancer patients were analyzed by Cox regression. Finally, JCAD was selected. Using virus to stably overexpress JCAD and shRNA technology to knock down JCAD, the function of JCAD for the proliferation and metastasis of breast cancer was discussed through CCK8 cell proliferation experiment, EdU cell proliferation experiment, plate cloning experiment, transwell cell migration experiment. T-test and chi square test were performed on the data. P &amp;lt; 0.05 showed that the difference was statistically significant. Kaplan-Meier survival was used to analyze the long-term efficacy. Result 1. The expression of JCAD mRNA in exosomes increased from benign to stage 4 (P &amp;lt; 0.001). In addition, patients with lymph node metastasis had significantly higher expression of exosome JCAD (p=0.009), and the prognosis of patients with high expression of exosome JCAD was poor (p=0.003). This conclusion has also been verified in TCGA database. Finally, Cox regression analysis showed that JCAD was an independent prognostic factor affecting PFS (p=0.005). 2. JCAD is transmitted between cells in the form of exosomes: In breast cancer cells, stable transgenic strains with overexpression of JCAD and shRNA knockdown strains of JCAD were constructed. The exosomes were extracted by ultracentrifugation for RNA and protein level verification. It shows that there was a difference in the expression of JCAD in the exosomes of overexpression and knockdown strains. After adding exosome inhibitor GW4869 to culture cells, it was found that the level of JCAD mRNA secreted by exosomes decreased significantly. In addition, through PKH26 exosome fluorescence labeling method, it was found that JCAD was transmitted between cells in the form of exosomes. 3. JCAD can promote the proliferation and migration of breast cancer cells: This experiment verified the ability of JCAD to promote the proliferation of breast cancer cells through CCK8 cell proliferation experiment, EdU cell proliferation experiment, plate cloning experiment. Then the ability of JCAD to promote the migration of breast cancer cells was verified by transwell cell migration experiment. The exosomes were added to wild type cells for co-culture. It was further found that the exosomes with high expression of JCAD could promote the proliferation and migration of breast cancer cells. Conclusion JCAD is significantly overexpressed in stage IV patients and patients with lymph node metastasis. Moreover, JCAD is an independent prognostic factor affecting PFS, and the exosome JCAD is expected to become a potential prognostic liquid biopsy marker. Further cell experiments showed that JCAD can be transmitted between breast cancer cells through exosomes and promote the proliferation and metastasis of breast cancer cells. Citation Format: Douwaner Liu, Yayun Chi, Bingqiu Xiu, Qi Zhang, Wei-Ru Chi, Liyi Zhang, Min Xiong, Jiong Wu. Correlation between the expression of JCAD in plasma exosomes and breast cancer [abstract]. In: Proceedings of the 2022 San Antonio Breast Cancer Symposium; 2022 Dec 6-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2023;83(5 Suppl):Abstract nr P3-05-24.

The Impact of Antiviral Treatment of Hepatitis B Virus after Kidney Transplant and the Latest Insights

The current frequency of hepatitis B virus infection in patients with advanced chronic kidney disease (CKD) (including patients on maintenance dialysis and kidney transplant recipients) is low but not negligible worldwide. HBV has a deleterious effect on survival after a kidney transplant; antiviral treatments improved the short-term outcomes of kidney transplant recipients, but their long-term impact remains uncertain. The aim of this review is to assess the role of antiviral therapy for HBV in improving survival after a kidney transplant. The recent publication of large surveys has prompted us to update the available evidence on the impact of HBV on patient and graft survival after a kidney transplant. We have conducted an extensive review of the medical literature, and various research engines have been used. We retrieved several studies (n = 11; n = 121,436 unique patients) and found an association between positive serologic HBsAg status and diminished patient and graft survival after a kidney transplant; the adjusted relative risk (aRR) of all-cause mortality and graft loss was 2.85 (95% CI, 2.36; 3.33, p < 0.0001) and 1.26 (95% CI, 1.02; 1.51, p < 0.0001), respectively. To our knowledge, at least six studies reported improved patient and graft survival after the adoption of antiviral therapies for HBV (this result was reported with both survival curves and multivariable regression). According to novel clinical guidelines, entecavir has been suggested as a 'first line' antiviral agent for the treatment of HBV after a kidney transplant. The recent availability of safe and effective antiviral drugs for the treatment of HBV has meant that the survival curves of HBsAg-positive patients on antiviral therapy and HBsAg-negative patients after a kidney transplant can be comparable. Antiviral therapy should be systematically proposed to HBV-positive kidney transplant recipients and candidates to avoid the deleterious hepatic and extra-hepatic effects of chronic HBV replication.

The Expression of Serum lncRNA MIR17HG in Patients with Multiple Myeloma and Its Clinical Significance

Objective. Multiple myeloma (MM) represents a malignant tumor with abnormal proliferation of plasma cells. The current study sought to investigate the changes in serum lncRNA MIR17HG (long noncoding RNA miR-17-92a-1 cluster host gene) levels in MM patients and its values in assessing the accuracy of MM diagnosis and predicting diagnosis. Methods. First, 108MM patients and 85 healthy controls were enrolled as the study subjects. The serum levels of MIR17HG in all subjects were determined by RT-qPCR. MM patients were clinically staged according to the Durie-Salmon (DS) and international staging system (ISS), and the levels of serum MIR17HG were compared among patients at different stages. The correlation of serum MIR17H level with serum creatinine (Scr), lactate dehydrogenase (LDH), and albumin (ALB) was analyzed using the Pearson method. The accuracy of the serum MIR17HG level in identifying MM was evaluated using receiver operating characteristic curves. The progression-free survival (PFS) and overall survival (OS) curves of MM patients were plotted using the Kaplan–Meier method. Results. Serum MIR17HG levels were up-regulated in MM patients and elevated with the development of DS and ISS stages. The serum MIR17HG was positively correlated with Scr and LDH and negatively correlated with ALB in MM patients. Serum MIR17HG level &gt;1.485 could evaluate the accuracy of identifying MM. The PFS and OS were significantly shortened in MM patients with elevated MIR17HG levels. Conclusion. Our findings collectively indicate that the serum MIR17HG can aid the evaluation of accurate MM identification, and a high serum MIR17HG level can predict poor prognosis of patients with MM.

Implant–Prosthetic Rehabilitation of Maxillary Lateral Incisor Agenesis with Narrow Diameter Implants and Metal–Ceramic vs. All-Ceramic Single Crowns: A 16-Year Prospective Clinical Study

The main objectives of the present prospective clinical study were to evaluate the marginal bone resorption and the peri-implant soft tissue conditions around narrow diameter implants, as well as the clinical performances of metal–ceramic and all-ceramic single crowns in the implant–prosthetic treatment of maxillary lateral incisors agenesis. Seventy-two patients affected by monolateral or bilateral agenesis of the maxillary lateral incisors were included in the study, and a total of 105 narrow diameter implants were inserted. The final single crowns were fabricated 4 months after the surgical procedures by means of either titanium abutments with Auro-Galvan Crowns (AGC) veneered with feldspathic ceramics or zirconia abutments with all-ceramic (alumina or zirconia) crowns layered with dedicated veneering ceramics. Both marginal bone resorption and soft tissue quality were evaluated after a maximum period of 16 years. Two independent survival curves for patients wearing AGC or all-ceramic crowns were calculated by means of Kaplan–Meier analysis, and a log-rank test was performed in order to compare these curves (p &lt; 0.05). After 16 years of clinical function, a mean marginal bone resorption of 1.2 ± 0.61 mm and good response of peri-implant soft tissues were observed. Descriptive statistics resulted in 80% and 87.1% cumulative success rates for patients provided with AGC prostheses onto titanium abutments and all-ceramic crowns on-to zirconia abutments, respectively. The cumulative survival rate calculated for AGC group was 93.3%, whereas all-ceramic group showed a cumulative survival rate of 95.7%. No statistically significant differences were found with the log-rank tests. The overall success and survival rates calculated were 85% and 95% for all the restorations, respectively. Mucositis, abutment unscrewing, loss of retention, chipping, core fracture, and esthetic failure were the major complications reported. The implant–prosthetic approach can be considered an effective and viable solution to treat cases of maxillary lateral incisor agenesis in the long term.

Prognostic prediction of clear cell renal cell carcinoma based on lipid metabolism-related lncRNA risk coefficient model.

Objective: In order to predict the prognosis in patients with clear cell renal cell carcinoma (ccRCC) so as to understand cancer lipid metabolism and sensitivity to immune-targeting drugs, model algorithms were used to establish a risk coefficient model of long non-coding RNAs (lncRNAs) associated with lipid metabolism. Methods: The transcriptome data were retrieved from TCGA, and lncRNAs associated with lipid metabolism were obtained through Pearson correlation and differential expression analyses. Differentially expressed lipid metabolism-related lncRNAs and lipid metabolism-related lncRNA pairs were obtained using the R language software. The minimum absolute shrinkage method and the selector operation regression method were used to construct the model and draw the receiver operator characteristic curve. High-risk patients were differentiated from low-risk patients through the cut-off value, and the correlation analyses of the high-risk subgroup and low-risk subgroup were performed. Results: This research discovered that 25 pairs of lncRNAs were associated with the lipid metabolism of ccRCC, and 12 of these pairs were utilized to build the model. In combination with clinical data, the areas under the 1-, 3- and 5-year survival curves of ccRCC patients were 0.809, 0.764 and 0.792, separately. The cut-off value was used to perform subgroup analysis. The results showed that high-risk patients had poor prognosis. The results of Cox multivariate regressive analyses revealed that age and risk score were independent prediction factors of ccRCC prognosis. In addition, immune cell infiltration, the levels of gene expression at immune checkpoints, and high-risk patients more susceptible to sunitinib-targeted treatment were assessed by the risk model. Conclusion: Our team identified new prognostic markers of ccRCC and established risk models that could assess the prognosis of ccRCC patients and help determine which type of patients were more susceptible to sunitinib. These discoveries are vital for the optimization of risk stratification and personalized management.

Comparison of the clinical efficacy of a new prognostic stratification for duodenal adenocarcinoma with that of TNM staging: The importance of T status with regard to the prognosis.

Although the current staging system and therapeutic strategy for duodenal adenocarcinoma (DA) focus on the N status, their validity has not been clarified. In this study, we evaluated the prognostic factors of DA and reviewed the current staging system. We included 105 patients who underwent surgical resection of DA in our department between September 2006 and October 2020. Patients with localised disease other than an early tumour (pT1a) were classified into the advanced group, and prognostic factors were compared with those for the Union for International Cancer Control (UICC) classification, 8th edition. The 5-year overall survival (OS) rate in the advanced group (n=55) was 73%. Multivariate analysis revealed that pT4 and pN2 statuses were independent prognostic factors for OS. The prognosis was stratified based on the pT4 and pN2 statuses, whereas the survival curves for patients with pStage II (pN0) and pStage IIIA (pN1) DA overlapped on staging according to the UICC classification. The new classification indicated a favourable prognosis for patients classified as pT1-3N1 stage IIIA (5-year OS, 86%), whereas the prognosis of patients with pT4N0-1 DA was similar to those classified as pT1-3N2 stage IIIB. Patients with pT4N2 DA had a similar prognosis (5-year OS, 24%) as those with metastases, and 75% of these patients showed distant metastasis within one year after surgery. Both T and N statuses affect the prognosis of DA. Patients with pT4N2 DA may require intensive adjuvant chemotherapy. (238 words).

PKNOX1 acts as a transcription factor of DHH and promotes the progression of stomach adenocarcinoma by regulating the Hedgehog signalling pathway.

This study explored the effects and potential mechanism by which PBX/knotted 1 homeobox 1 (PKNOX1) may exacerbate stomach adenocarcinoma (STAD). For the in silico analysis, we examined TCGA-PKNOX1 expression using the UALCAN website, as well as its expression patterns in the GSE172032 and GSE174237 datasets, obtained from the GEO database. The associated patient survival curves, were analysed via the KMplot webtool. In vitro, we measured cell viability, proliferation, migration, and invasion using cell counting kit-8, colony formation, wound healing, and cell migration assays, respectively. Real time qPCR and western blotting assessed the mRNA and protein levels of PKNOX1, Snail, vimentin, N-cadherin, E-cadherin, desert hedgehog (DHH), cyclin D2, glioma-associated oncogene homolog 1, and smoothened. Gene Set Enrichment Analysis was performed using LinkedOmics webtools and the clusterProfiler package in R. Dual-luciferase reporter assay was used to examine the interactions of PKNOX1 with DHH, and of TEA domain transcription factor 4 (TEAD4) with PKNOX1. PKNOX1 was highly expressed in STAD and linked to poor patient survival. Downregulation of PKNOX1 inhibited STAD cell viability, proliferation, migration, invasion, and epithelial-mesenchymal transition. Upregulation of TEAD4 promoted colony formation and migration, while these effects were reversed by PKNOX1 depletion. Furthermore, PKNOX1 regulated the activation of the hedgehog signalling pathway at the gene level, as we identified PKNOX1 to be a putative transcription factor for DHH that promotes its expression. Our results show that PKNOX1 acts as a candidate transcription factor for DHH and facilitates STAD development by regulating the hedgehog signalling pathway.

Machine Learning-Based Scoring System for Early Prognosis Evaluation of Patients with Coronavirus Disease 2019

Abstract Background The global spread of coronavirus disease 2019 (COVID-19) continues to threaten human health security, exerting considerable pressure on healthcare systems worldwide. While prognostic models for COVID-19 hospitalized or intensive care patients are currently available, prognostic models developed for large cohorts of thousands of individuals are still lacking. Methods Between February 4 and April 16, 2020, we enrolled 3,974 patients admitted with COVID-19 disease in the Wuhan Huo-Shen-Shan Hospital and the Maternal and Child Hospital, Hubei Province, China. (1) Screening of key prognostic factors: A univariate Cox regression analysis was performed on 2,649 patients in the training set, and factors affecting prognosis were initially screened. Subsequently, a random survival forest model was established through machine analysis to further screen for factors that are important for prognosis. Finally, multivariate Cox regression analysis was used to determine the synergy among various factors related to prognosis. (2) Establishment of a scoring system: The nomogram algorithm established a COVID-19 patient death risk assessment scoring system for the nine selected key prognostic factors, calculated the C index, drew calibration curves and drew training set patient survival curves. (3) Verification of the scoring system: The scoring system assessed 1,325 patients in the test set, splitting them into high- and low-risk groups, calculated the C-index, and drew calibration and survival curves. Results The cross-sectional study found that age, clinical classification, sex, pulmonary insufficiency, hypoproteinemia, and four other factors (underlying diseases: blood diseases, malignant tumor; complications: digestive tract bleeding, heart dysfunction) have important significance for the prognosis of the enrolled patients with COVID-19. Herein, we report the discovery of the effects of hypoproteinemia and hematological diseases on the prognosis of COVID-19. Meanwhile, the scoring system established here can effectively evaluate objective scores for the early prognoses of patients with COVID-19 and can divide them into high- and low-risk groups (using a scoring threshold of 117.77, a score below which is considered low risk). The efficacy of the system was better than that of clinical classification using the current COVID-19 guidelines (C indexes, 0.95 vs. 0.89). Conclusions Age, clinical typing, sex, pulmonary insufficiency, hypoproteinemia, and four other factors were important for COVID-19 survival. Compared with general statistical methods, this method can quickly and accurately screen out the relevant factors affecting prognosis, provide an order of importance, and establish a scoring system based on the nomogram model, which is of great clinical significance.

Biomarkers of cell damage, neutrophil and macrophage activation associated with in-hospital mortality in geriatric COVID-19 patients

BackgroundThe risk for symptomatic COVID-19 requiring hospitalization is higher in the older population. The course of the disease in hospitalised older patients may show significant variation, from mild to severe illness, ultimately leading to death in the most critical cases. The analysis of circulating biomolecules involved in mechanisms of inflammation, cell damage and innate immunity could lead to identify new biomarkers of COVID-19 severity, aimed to improve the clinical management of subjects at higher risk of severe outcomes.In a cohort of COVID-19 geriatric patients (n= 156) who required hospitalization we analysed, on-admission, a series of circulating biomarkers related to neutrophil activation (neutrophil elastase, LL-37), macrophage activation (sCD163) and cell damage (nuclear cfDNA, mithocondrial cfDNA and nuclear cfDNA integrity). The above reported biomarkers were tested for their association with in-hospital mortality and with clinical, inflammatory and routine hematological parameters. Aim of the study was to unravel prognostic parameters for risk stratification of COVID-19 patients.ResultsLower n-cfDNA integrity, higher neutrophil elastase and higher sCD163 levels were significantly associated with an increased risk of in-hospital decease. Median (IQR) values observed in discharged vs. deceased patients were: 0.50 (0.30-0.72) vs. 0.33 (0.22-0.62) for n-cfDNA integrity; 94.0 (47.7-154.0) ng/ml vs. 115.7 (84.2-212.7) ng/ml for neutrophil elastase; 614.0 (370.0-821.0) ng/ml vs. 787.0 (560.0-1304.0) ng/ml for sCD163. The analysis of survival curves in patients stratified for tertiles of each biomarker showed that patients with n-cfDNA integrity < 0.32 or sCD163 in the range 492-811 ng/ml had higher risk of in-hospital decease than, respectively, patients with higher n-cfDNA integrity or lower sCD163. These associations were further confirmed in multivariate models adjusted for age, sex and outcome-related clinical variables. In these models also high levels of neutrophil elastase (>150 ng/ml) appeared to be independent predictor of in-hospital death. An additional analysis of neutrophil elastase in patients stratified for n-cfDNA integrity levels was conducted to better describe the association of the studied parameters with the outcome.ConclusionsOn the whole, biomarkers of cell-free DNA integrity, neutrophil and macrophage activation might provide a valuable contribution to identify geriatric patients with high risk of COVID-19 in-hospital mortality.

SLFN11 Is a Potential Biomarker and Modulator of Treatment Response in AML

Introduction: Despite recent advances in treatment for acute myeloid leukemia (AML), AML remains a deadly disease, with approximately 70% of patients succumbing to the disease within five years of diagnosis (SEER database 2021). Intensive induction chemotherapy carries a risk of morbidity and mortality, making it a risky treatment for patients who are unlikely to achieve a remission with DNA damaging-based treatments. Hypomethylating agents (HMAs) such as azacitidine (AZA) and decitabine (DAC) are now frequently used in AML treatment as less intensive treatment options. Thus, biomarkers to predict response to DNA damaging agents in AML are needed. We recently found a significant association between AML patient survival and high expression of Schlafen11 (SLFN11), a dynamically inducible key effector of the DNA replication stress response. SLFN11 has been shown to be associated with response to certain chemotherapy agents in some solid tumors in vitro and in vivo (Conteduca et. al. JCO 2019; Shee et. al. PLoS One 2019), but its importance in leukemia has not been well defined. It is also unknown whether SLFN11 levels affect response to HMAs. We hypothesized that SLFN11 can be used as a predictive biomarker for treatment response to DNA-damaging agents in AML but that response to HMAs would be independent of HMAs. We also hypothesized that identifying pathways upregulated in SLFN11-low cells could lead to novel combination therapies to increase sensitivity to chemotherapeutics. Methods: The human leukemia cell lines HEL and U937 cells were used for these studies. U937- and HEL-SLFN11 knockout (SLFN11KO) cells were generated using CRISPR-Cas9 gene editing technology. Cell viability was assessed by WST-1 reagent assay. SLFN11 and other protein levels were measured by Western blotting. Results: SLFN11 protein expression was readily observed by immunoblotting of HEL and U937 cell lysates. U937- and HEL-SLFN11KO cells were incubated with increasing concentrations of cytarabine (AraC), which is the backbone of most chemotherapy regimens currently used in AML treatment. Both U937- and HEL-SLFN11KO cells were more resistant to AraC than their respective control cells. To examine the mechanism of resistance in U937-SLFN11KO cells, SLFN11KO and control cells were treated with AraC for up to 8 hrs, and lysates were subjected to immunoblotting for various DNA damage response proteins. There were higher baseline levels of multiple DNA damage-related proteins (including Chk1 and Chk2) in the SLFN11KO cells. There was also prolonged activation of the DNA damage pathway in U937-SLFN11KO cells, as evidenced by phosphorylation of the ATR substrate Chk1 (Ser345) through 8 hours, whereas phospho-Chk1 levels decreased in control cells by 8 hours. Interestingly, this prolonged activation occurred without a concomitant increase in γH2AX (a marker of DNA damage and double strand breaks). Because U937-SLFN11KO cells demonstrated a more pronounced activation of the ATR/Chk1 pathway in response to AraC, we subjected U937-SLFN11KO and control cells to increasing concentrations of AraC in combination with a small dose (0.3 μM) of the ATR inhibitor VE822. Notably, ATR inhibition restored sensitivity of SLFN11KO cells to AraC. These results suggest that SLFN11KO cells are resistant to DNA damaging agents via upregulation and activation of DNA repair proteins, and that adding inhibitors of these proteins can decrease resistance to chemotherapy agents in SLFN11KO cells. In contrast, SLFN11KO cells remained sensitive to AZA and DAC, suggesting that HMAs may be preferable to AraC for patients with SLFN11-low AML. Conclusions: Low SLFN11 levels predict poor response to standard chemotherapy agents (i.e. AraC) in AML cells, suggesting that SLFN11 may prove to be an important predictive biomarker for AML patients. In addition, SLFN11-low AML cells have an increased reliance on DNA repair pathways, and inhibition of DNA repair proteins such as ATR may enhance responses to AraC in these cells. This raises the possibility of patient selection based on SLFN11 levels for specific combination approaches for the treatment of AML. Figure 1. Kaplan Meier survival curves of AML patients in the TCGA (LAML) database with high (top 50th percentile) or low (bottom 50th percentile) SLFN11 expression using UCSC Xena (Goldman et. al. Nat Biotechnol 2020). Figure 1View largeDownload PPTFigure 1View largeDownload PPT Close modal

DDDR-27. A PATIENT-DERIVED DRUG SCREENING PLATFORM PREDICTS RESPONSE TO TEMOZOLOMIDE AND IDENTIFIES POTENTIAL NEW TREATMENTS FOR GLIOBLASTOMA

Abstract BACKGROUND Major obstacles that have impeded the development of effective new therapies for GBM include inter- and intratumoral heterogeneity, the blood-brain-barrier and use of sub-optimal cell line-based preclinical models. Taking these hurdles into account, we have set up a patient-derived GBM drug-screening platform. We optimized protocols to improve cell culture success rate and retrospectively assessed the predictive power of our assay for patient response to TMZ. A large panel of GBM cells was screened for sensitivity to available oncological agents. Drugs of interest were selected based on favorable physicochemical properties for BBB crossing and potent activity in (a subset of) GBM cultures. Finally, we determined the success rate of performing a small-scale screen with 20 selected agents within 4 weeks of receiving tumor tissue. RESULTS By combining both CUSA and tissue piece-derived dissociation protocols, culture success increased to 95%, ensuring representation of the near-complete spectrum of GBM subtypes. Single-cell sequencing studies confirmed heterogeneity in our low-passage cell cultures. In vitro screening of TMZ on a large cohort (n = 55) identified 3 response categories (responders/intermediates/non-responders) for which Cox regression analysis revealed significantly different overall survival curves of corresponding patients. Screening of 107 FDA-approved anticancer agents on 45 GBM cultures underscored the tremendous intertumoral heterogeneity in drug sensitivities. We identified 20 potent agents each effective at clinically-achievable concentrations in (a subset of) GBM cultures and having favorable BBB penetration properties (CNS-MPO score). Screening of these agents on a per patient basis within 4 weeks of receiving tissue was successful in 18 out of 24 (75%) tested tumors. In the remaining cases the tumor cells grew very slowly and longer culture times were required. CONCLUSION Our drug screening platform offers a tool to predict TMZ response and assess sensitivity to candidate treatments, either for GBM subsets or on a per patient basis.

Significance analysis of PAX8 expression in endometrial carcinoma.

To analyze the expression and prognostic value of paired-box 8 (PAX8) expression in uterine corpus endometrial carcinoma (UCEC) by bioinformatics. The expression of PAX8 gene in UCEC was analyzed by R language and immunohistochemistry. The correlation between PAX8 expression and clinicopathological features was analyzed by R language. The prognostic factors was analyzed by univariate/multivariate regression. The survival curve of patients was analyzed by Kaplan–Meier Plotter (K–M Plotter). The diagnostic value of PAX8 in UCEC was analyzed by receiver operating characteristic curve, and the relationship between PAX8 expression and methylation was analyzed by Ualcan. The relationship between methylation and prognosis was analyzed by MethSurv database. The expression of PAX8 in cancer tissues was significantly higher than that in normal tissues. The expression of PAX8 was related to clinical stage, age, histological type, histologic grade, tumor invasion and disease-specific survival event. Univariate/multivariate regression analysis showed that clinical stage, tumor invasion, and PAX8 expression were the influence factors of overall survival (OS), while histologic grade and PAX8 expression were the influence factors of disease-specific survival, and patients with low expression had a longer OS. The area under the curve of receiver operating characteristic curve was 0.81 for PAX8 diagnosis of UCEC. PAX8 was hypomethylated in cancer tissue, and patients with hypermethylated PAX8 had a longer OS. The high expression of PAX8 induced by hypomethylation may play an important role in the occurrence and prognosis of UCEC.