Image_1_Development and validation of lymph node ratio-based nomograms for primary duodenal adenocarcinoma after surgery.tif

BackgroundThe prediction models for primary duodenal adenocarcinoma (PDA) are deficient. This study aimed to determine the predictive value of the lymph node ratio (LNR) in PDA patients and to establish and validate nomograms for predicting overall survival (OS) and cancer-specific survival (CSS) for PDAs after surgical resection.MethodsWe extracted the demographics and clinicopathological information of PDA patients between 2004 and 2018 from the Surveillance, Epidemiology and End Results database. After screening cases, we randomly divided the enrolled patients into training and validation groups. X-tile software was used to obtain the best cut-off value for the LNR. Univariate and multivariate Cox analyses were used in the training group to screen out significant variables to develop nomograms. The predictive accuracy of the nomograms was evaluated by the concordance index (C-index), calibration curves, area under the receiver operating characteristic curve (AUC) and decision curve analysis (DCA). Finally, four risk groups were created based on quartiles of the model scores.ResultsA total of 978 patients were included in this study. The best cut-off value for the LNR was 0.47. LNR was a negative predictive factor for both OS and CSS. Age, sex, grade, chemotherapy and LNR were used to construct the OS nomogram, while age, grade, chemotherapy, the number of lymph nodes removed and LNR were incorporated into the CSS nomogram. The C-index, calibration curves and AUC of the training and validation sets revealed their good predictability. DCA showed that the predictive value of the nomograms was superior to that of the American Joint Committee on Cancer (AJCC) TNM staging system (8th edition). In addition, risk stratification demonstrated that patients with higher risk correlated with poor survival.ConclusionsThe LNR was an adverse prognostic determinant for PDAs. The nomograms provided an accurate and applicable tool to evaluate the prognosis of PDA patients after surgery.</p

Image_2_Development and validation of lymph node ratio-based nomograms for primary duodenal adenocarcinoma after surgery.tif

BackgroundThe prediction models for primary duodenal adenocarcinoma (PDA) are deficient. This study aimed to determine the predictive value of the lymph node ratio (LNR) in PDA patients and to establish and validate nomograms for predicting overall survival (OS) and cancer-specific survival (CSS) for PDAs after surgical resection.MethodsWe extracted the demographics and clinicopathological information of PDA patients between 2004 and 2018 from the Surveillance, Epidemiology and End Results database. After screening cases, we randomly divided the enrolled patients into training and validation groups. X-tile software was used to obtain the best cut-off value for the LNR. Univariate and multivariate Cox analyses were used in the training group to screen out significant variables to develop nomograms. The predictive accuracy of the nomograms was evaluated by the concordance index (C-index), calibration curves, area under the receiver operating characteristic curve (AUC) and decision curve analysis (DCA). Finally, four risk groups were created based on quartiles of the model scores.ResultsA total of 978 patients were included in this study. The best cut-off value for the LNR was 0.47. LNR was a negative predictive factor for both OS and CSS. Age, sex, grade, chemotherapy and LNR were used to construct the OS nomogram, while age, grade, chemotherapy, the number of lymph nodes removed and LNR were incorporated into the CSS nomogram. The C-index, calibration curves and AUC of the training and validation sets revealed their good predictability. DCA showed that the predictive value of the nomograms was superior to that of the American Joint Committee on Cancer (AJCC) TNM staging system (8th edition). In addition, risk stratification demonstrated that patients with higher risk correlated with poor survival.ConclusionsThe LNR was an adverse prognostic determinant for PDAs. The nomograms provided an accurate and applicable tool to evaluate the prognosis of PDA patients after surgery.</p

Table_1_Development and validation of lymph node ratio-based nomograms for primary duodenal adenocarcinoma after surgery.doc

BackgroundThe prediction models for primary duodenal adenocarcinoma (PDA) are deficient. This study aimed to determine the predictive value of the lymph node ratio (LNR) in PDA patients and to establish and validate nomograms for predicting overall survival (OS) and cancer-specific survival (CSS) for PDAs after surgical resection.MethodsWe extracted the demographics and clinicopathological information of PDA patients between 2004 and 2018 from the Surveillance, Epidemiology and End Results database. After screening cases, we randomly divided the enrolled patients into training and validation groups. X-tile software was used to obtain the best cut-off value for the LNR. Univariate and multivariate Cox analyses were used in the training group to screen out significant variables to develop nomograms. The predictive accuracy of the nomograms was evaluated by the concordance index (C-index), calibration curves, area under the receiver operating characteristic curve (AUC) and decision curve analysis (DCA). Finally, four risk groups were created based on quartiles of the model scores.ResultsA total of 978 patients were included in this study. The best cut-off value for the LNR was 0.47. LNR was a negative predictive factor for both OS and CSS. Age, sex, grade, chemotherapy and LNR were used to construct the OS nomogram, while age, grade, chemotherapy, the number of lymph nodes removed and LNR were incorporated into the CSS nomogram. The C-index, calibration curves and AUC of the training and validation sets revealed their good predictability. DCA showed that the predictive value of the nomograms was superior to that of the American Joint Committee on Cancer (AJCC) TNM staging system (8th edition). In addition, risk stratification demonstrated that patients with higher risk correlated with poor survival.ConclusionsThe LNR was an adverse prognostic determinant for PDAs. The nomograms provided an accurate and applicable tool to evaluate the prognosis of PDA patients after surgery.</p

DataSheet_1_A multi-subgroup predictive model based on clinical parameters and laboratory biomarkers to predict in-hospital outcomes of plasma exchange-centered artificial liver treatment in patients with hepatitis B virus-related acute-on-chronic liver failure.docx

BackgroundPostoperative risk stratification is challenging in patients with hepatitis B virus-related acute-on-chronic liver failure (HBV-ACLF) who undergo artificial liver treatment. This study characterizes patients’ clinical parameters and laboratory biomarkers with different in-hospital outcomes. The purpose was to establish a multi-subgroup combined predictive model and analyze its predictive capability.MethodsWe enrolled HBV-ACLF patients who received plasma exchange (PE)-centered artificial liver support system (ALSS) therapy from May 6, 2017, to April 6, 2022. There were 110 patients who died (the death group) and 110 propensity score-matched patients who achieved satisfactory outcomes (the survivor group). We compared baseline, before ALSS, after ALSS, and change ratios of laboratory biomarkers. Outcome prediction models were established by generalized estimating equations (GEE). The discrimination was assessed using receiver operating characteristic analyses. Calibration plots compared the mean predicted probability and the mean observed outcome.ResultsWe built a multi-subgroup predictive model (at admission; before ALSS; after ALSS; change ratio) to predict in-hospital outcomes of HBV-ACLF patients who received PE-centered ALSS. There were 110 patients with 363 ALSS sessions who survived and 110 who did not, and 363 ALSS sessions were analyzed. The univariate GEE models revealed that several parameters were independent risk factors. Clinical parameters and laboratory biomarkers were entered into the multivariate GEE model. The discriminative power of the multivariate GEE models was excellent, and calibration showed better agreement between the predicted and observed probabilities than the univariate models.ConclusionsThe multi-subgroup combined predictive model generated accurate prognostic information for patients undergoing HBV-ACLF patients who received PE-centered ALSS.</p

Depletion of Paraspeckle Protein 1 Enhances Methyl Methanesulfonate-Induced Apoptosis through Mitotic Catastrophe

<div><p>Previously, we have shown that paraspeckle protein 1 (PSPC1), a protein component of paraspeckles that was involved in cisplatin-induced DNA damage response (DDR), probably functions at the G1/S checkpoint. In the current study, we further examined the role of PSPC1 in another DNA-damaging agent, methyl methanesulfonate (MMS)-induced DDR, in particular, focusing on MMS-induced apoptosis in HeLa cells. First, it was found that MMS treatment induced the expression of PSPC1. While MMS treatment alone can induce apoptosis, depletion of PSPC1 expression using siRNA significantly increased the level of apoptosis following MMS exposure. In contrast, overexpressing PSPC1 decreased the number of apoptotic cells. Interestingly, morphological observation revealed that many of the MMS-treated PSPC1-knockdown cells contained two or more nuclei, indicating the occurrence of mitotic catastrophe. Cell cycle analysis further showed that depletion of PSPC1 caused more cells entering the G2/M phase, a prerequisite of mitosis catastrophe. On the other hand, over-expressing PSPC1 led to more cells accumulating in the G1/S phase. Taken together, these observations suggest an important role for PSPC1 in MMS-induced DDR, and in particular, depletion of PSPC1 can enhance MMS-induced apoptosis through mitotic catastrophe.</p></div

Cell viability and DNA damage were determined after methyl methanesulfonate (MMS) treatment.

<p>(A) HeLa cells were treated with the indicated concentrations of MMS for 12, 24, 36, and 48 h. Cell viability was measured by MTT assay. (B) HeLa cells were treated with different concentrations of MMS for 12 h, then detected the level of DNA damage by immunofluorescence (a) and Western blot (b). Scale bar, 50 μm. The results are shown as the mean ± SD of three independent experiments. *p < 0.05, **p < 0.01, as compared with the solvent control group.</p

Modulation of PSPC1 influences MMS-induced cell cycle redistribution.

<p>(A) HeLa cells were transfected with siPSPC1 or siControl for 24 h, then treated with 0 μM and 100 μM of MMS for 12 h. The expression of PSPC1 was examined by Western blot and cell cycle was analyzed by flow cytometry. (B) HeLa cells were transfected with pPSPC1 or pCON to overexpress PSPC1 for 24 h, then treated with 0 μM and 100 μM of MMS for 12 h. The expression of PSPC1 was examined by Western blot and cell cycle was analyzed by flow cytometry. The values represent averages of three independent experiments, mean ± SD.*p < 0.05, **p < 0.01, as compared with the control group.</p

Knockdown of PSPC1 induces mitotic catastrophe.

<p>HeLa cells were transfected with siPSPC1 or siControl. 24 h post-transfection, cells were harvested and the expression of tubulin and the nucleolus were examined by immunofluorescence microscopy (A). The percentage of multinuclear cells were shown as a histogram, and densitometry data of three independent experiments were presented, mean ± SD (n = 200 cells). (B). (C) Using the same treated cells, the levels of representative mitotic catastrophe proteins (phospho-histone H3 [Ser10], Cdc2, cyclinB, and Chk2) were examined by western blot. **p < 0.01, as compared with the control group.</p

Paraspeckle protein 1 (PSPC1) is induced by MMS.

<p>HeLa cells were treated with indicated concentrations of MMS for 12 h. The levels of PSPC1 were examined by Western blot. The results are shown as the mean ± SD of three independent experiments. *p < 0.05, as compared with the control group.</p

Effect of PSPC1 on MMS-induced apoptosis.

<p>(A) HeLa cells were transfected with siPSPC1, siControl, pPSPC1, or pControl for 24 h, followed by 200 or 400 μM of MMS treatment for 12 h prior to analysis of PSPC1 and PARP expression by Western blot. For the detection of apoptosis, HeLa cells transfected with siRNAs (B) or overexpression plasmids (C) were treated with 200 or 400 μM of MMS for 12 h, and then analyzed by dual-parameter flow cytometry utilizing Annexin V-FITC and PI double staining. Representative dot plot data from three independent experiments are shown in the left panel, and the histogram graph in the right panel represents the percentage of dual-parameter positive cells pooled from three independent experiments. Data are presented as the mean ± SD of three independent experiments. **p < 0.01, as compared with the control group.</p