ART1 knockdown decreases the IL-6-induced proliferation of colorectal cancer cells.

Colorectal cancer (CRC) is a worldwide health concern. Chronic inflammation is a risk factor for CRC, and interleukin-6 (IL-6) plays a pivotal role in this process. Arginine-specific mono-ADP-ribosyltransferase-1 (ART1) positively regulates inflammatory cytokines. ART1 knockdown reduces the level of glycoprotein 130 (gp130), a key transducer in the IL-6 signalling pathway. However, the relationship between ART1 and IL-6 and the resulting effects on IL-6-induced proliferation in CRC cells remain unclear. The aims of this study were to investigate the effects of ART1 knockdown on IL-6-induced cell proliferation in vitro and use an in vivo murine model to observe the growth of transplanted tumours. The results showed that compared with the control, ART1-sh cancer cells induced by IL-6 exhibited reduced viability, a lower rate of colony formation, less DNA synthesis, decreased protein levels of gp130, c-Myc, cyclin D1, Bcl-xL, and a reduced p-STAT3/STAT3 ratio (P < 0.05). Moreover, mice transplanted with ART1-sh CT26 cells that had high levels of IL-6 displayed tumours with smaller volumes (P < 0.05). ART1 and gp130 were colocalized in CT26, LoVo and HCT116 cells, and their expression was positively correlated in human CRC tissues. Overall, ART1 may serve as a promising regulatory factor for IL-6 signalling and a potential therapeutic target for human CRC.

Geriatric Nutritional Risk Index Combined with Calf Circumference Can be a Good Predictor of Prognosis in Patients Undergoing Surgery for Gastric or Colorectal Cancer.

OBJECTIVES: To explore the effect of combined hematological and physical measurement indicators on the prognosis of patients undergoing surgery for gastric or colorectal cancer and to screen for the best prognostic indicators. INTRODUCTION: Gastric and colorectal cancer is a widespread health concern worldwide and one of the major contributors to cancer-related death. The hematological and physical measurement indicators have been shown to associate with the prognosis of patients undergoing surgery for gastric or colorectal cancer, respectively, but it is still unclear whether the combination of the two can reflect the prognosis more effectively. METHODS: Thirteen hematological indicators and 5 physical measurement indicators were selected in this study, and the most promising ones were screened using LASSO regression. Then, the best prognostic indicators were selected by time-ROC curves. Survival curves were constructed using the Kaplan-Meier method, and the effects of hematological and physical measurement indicators on the prognosis of patients undergoing surgery for gastric or colorectal cancers were evaluated by Cox proportional risk regression analysis. In addition, the relationship between hematological and physical measurement indicators on secondary outcomes, including length of stay, hospitalization costs, intensive care unit (ICU) admission, and patients' subjective global assessment scores (PGSGA), was explored. RESULTS: After initial screening, among the hematological indicators, the geriatric nutritional risk index (GNRI) showed the highest mean area under the curve (AUC) values. Among body measures, calf circumference (CC) showed the highest mean AUC value. Further analyses showed that the combination of combined nutritional prognostic index (GNRI) and calf circumference (CC) (GNRI-CC) had the best performance in predicting the prognosis of patients undergoing surgery for gastric or colorectal cancers. Low GNRI, low CC, and low GNRI-low CC increased the risk of death by 44%, 48%, and 104%, respectively. Sensitivity analyses showed the same trend. In addition, low GNRI-low CC increased the risk of malnutrition by 17%. CONCLUSION: This study emphasizes that a combination of blood measures and body measures is essential to accurately assess the prognosis of patients undergoing surgery for gastric or colorectal cancers. The GNRI-CC is a good prognostic indicator and can also assess the risk of possible malnutrition.

Association of systemic inflammation with the obesity paradox in cancer: results from multi-cohort studies.

AIMS: This study aimed to explore whether the obesity paradox exists in overall and specific cancers and to investigate the role of systemic inflammation in the obesity paradox. METHODS: The Cox proportional hazard model was used to explore the relationship between body mass index (BMI) and all-cause mortality. The mediated effect was used to investigate the proportion of systemic inflammation mediating the relationship between BMI and cancer survival risk. RESULTS: The survival probability showed a step-like increase with an increase in BMI regardless of pathological stage. Approximately 10.8%-24.0% of the overall association between BMI and all-cause mortality in cancer was mediated by inflammation. In the internal validation, we found evidence of the obesity paradox in all body composition obtained using BIA, with inflammation remaining an important mediating factor. Furthermore, we also validated the existence of the obesity paradox of cancer in NHANES. Systemic inflammation remains an important factor in mediating the association between BMI and prognosis in cancer patients. CONCLUSIONS: The obesity paradox is prevalent in most cancers, except for hepatic biliary cancer and breast cancer. Inflammation may be one of the true features of the obesity paradox in cancer.

Remnant cholesterol is an effective biomarker for predicting survival in patients with breast cancer.

BACKGROUND: Breast cancer is the most common malignancy in women worldwide. The relationship between remnant cholesterol (RC) and the prognosis of patients with breast cancer has not been clearly reported. This study investigated the prognostic value of RC in predicting mortality in patients with breast cancer. METHODS: This study prospectively analysed 709 women patients with breast cancer from the Investigation on Nutrition Status and Clinical Outcome of Common Cancers (INSCOC) project. Restricted cubic splines were used to analyse the dose-response relationship between RC and breast cancer mortality. The Kaplan-Meier method was used to evaluate the overall survival of patients with breast cancer. A Cox regression analyses was performed to assess the independent association between RC and breast cancer mortality. Inverse probability of treatment weighting (IPTW) using the propensity score was used to reduce confounding. Sensitivity analysis was performed after excluding patients with underlying diseases and survival times shorter than one year. RESULTS: A linear dose-response relationship was identified between RC and the risk of all-cause mortality in patients with breast cancer (p = 0.036). Kaplan-Meier survival analysis and log-rank test showed that patients with high RC levels had poorer survival than those with low RC levels (p = 0.007). Univariate and multivariate Cox regression analyses showed that RC was an independent risk factor for mortality in women patients with breast cancer. IPTW-adjusted analyses and sensitivity analyses showed that CR remained a prognostic factor. CONCLUSIONS: RC is an independent risk factor for the prognosis of patients with breast cancer, and patients with higher RC levels have poorer survival.

Cholesterol-modified prognostic nutritional index (CPNI) as an effective tool for assessing the nutrition status and predicting survival in patients with breast cancer.

BACKGROUND: Malnutrition is associated with poor overall survival (OS) in breast cancer patients; however, the most predictive nutritional indicators for the prognosis of patients with breast cancer are not well-established. This study aimed to compare the predictive effects of common nutritional indicators on OS and to refine existing nutritional indicators, thereby identifying a more effective nutritional evaluation indicator for predicting the prognosis in breast cancer patients. METHODS: This prospective study analyzed data from 776 breast cancer patients enrolled in the "Investigation on Nutritional Status and its Clinical Outcome of Common Cancers" (INSCOC) project, which was conducted in 40 hospitals in China. We used the time-dependent receiver operating characteristic curve (ROC), Kaplan-Meier survival curve, and Cox regression analysis to evaluate the predictive effects of several nutritional assessments. These assessments included the patient-generated subjective nutrition assessment (PGSGA), the global leadership initiative on malnutrition (GLIM), the controlling nutritional status (CONUT), the nutritional risk index (NRI), and the prognostic nutritional index (PNI). Utilizing machine learning, these nutritional indicators were screened through single-factor analysis, and relatively important variables were selected to modify the PNI. The modified PNI, termed the cholesterol-modified prognostic nutritional index (CPNI), was evaluated for its predictive effect on the prognosis of patients. RESULTS: Among the nutritional assessments (including PGSGA, GLIM, CONUT, NRI, and PNI), PNI showed the highest predictive ability for patient prognosis (time-dependent ROC = 0.58). CPNI, which evolved from PNI, emerged as the superior nutritional index for OS in breast cancer patients, with the time-dependent ROC of 0.65. It also acted as an independent risk factor for mortality (p < 0.05). Moreover, the risk of malnutrition and mortality was observed to increase gradually among both premenopausal and postmenopausal age women, as well as among women categorized as non-overweight, overweight, and obese. CONCLUSIONS: The CPNI proves to be an effective nutritional assessment tool for predicting the prognosis of patients with breast cancer.

An integrated analysis of Dynamin 1 Like: A new potential prognostic indicator in hepatocellular carcinoma.

Dynamin 1 Like (DNM1L), a member of dynamin superfamily capable of mediating mitochondrial outer membrane division, plays a key role in the progression of different types of tumors. However, the prognostic value, clinical significance of DNM1L and its specific mechanism involved in tumorigenesis of hepatocellular carcinoma (HCC) have not been investigated clearly. In this study, we found that the expression of DNM1L were significantly higher in HCC tissues than adjacent/normal liver tissues based on multiple data sets obtained from TCGA, GEO and ONCOMINE database, also its protein expression form Drp1 is significantly higher in HCC tissues than adjacent tissues, and is related to the degree of differentiation. Kaplan-Meier curves suggested that high DNM1L expression prominently correlated with poorer overall survival, progression-free survival, relapse-free survival and disease-specific survival. Multivariate analysis showed that higher DNM1L expression was independent prognostic factors of shorter overall survival and disease-free survival. Kyoto Encyclopedia of Genes and Genomes and Gene set enrichment analysis analysis combined with validation experiments revealed the regulatory role of DNM1L on key molecules in the metabolism of xenobiotics by cytochrome p450 pathway, and DNM1L may also affects invasion and metastasis capability of HCC by mediating extracellular matrix -receptor interaction pathway. Moreover, analysis showed that higher DNM1L, CYP2C9, CYP3A4, CYP1A2 expression were associated with the resistance to sorafenib therapy. TIMER and CIBERSORT analysis indicated that the increase of DNM1L expression may affect the infiltration of immune cells in the tumor microenvironment. Taken together, the above results indicated that DNM1L could be able to serve as a promising independent predictor and therapeutic target for HCC patients.

Muscle distribution in relation to all-cause and cause-specific mortality in young and middle-aged adults.

BACKGROUND: The relationship between muscle and prognosis, especially that between muscle distribution across different body parts, and the related prognosis is not well established. OBJECTIVE: To investigate the relationship between muscle distribution and all-cause and cause-specific mortality and their potential modifiers. DESIGN: Longitudinal cohort study. C-index, IDI, and NRI were used to determine the best indicator of prognosis. COX regression analysis was performed to explore the relationship between variables and outcomes. Interaction and subgroup analyses were applied to identify the potential modifiers. PARTICIPANTS: A total of 5052 participants (weighted: 124,841,420) extracted from the NHANES 2003-2006 of median age 45 years and constituting 50.3% men were assessed. For validation, we included 3040 patients from the INSCOC cohort in China. MAIN MEASURES: Muscle mass and distribution. KEY RESULTS: COX regression analysis revealed that upper limbs (HR = 0.41, 95% CI 0.33-0.51), lower limbs (HR = 0.54, 95% CI 0.47-0.64), trunk (HR = 0.71, 95% CI, 0.59-0.85), gynoid (HR = 0.47, 95% CI 0.38-0.58), and total lean mass (HR = 0.55, 95% CI 0.45-0.66) were all associated with the better survival of participants (P trend < 0.001). The changes in the lean mass ratio of the upper and lower limbs and the lean mass ratio of the android and gynoid attenuated the protective effect of lean mass. Age and sex acted as potential modifiers, and the relationship between lean mass and the prognosis was more significant in men and middle-aged participants when compared to that in other age groups. Sensitive analyses depicted that despite lean mass having a long-term impact on prognosis (15 years), it has a more substantial effect on near-term survival (5 years). CONCLUSION: Muscle mass and its distribution affect the prognosis with a more significant impact on the near-term than that on the long-term prognosis. Age and sex acted as vital modifiers.

The value of CRP-albumin-lymphocyte index (CALLY index) as a prognostic biomarker in patients with non-small cell lung cancer.

OBJECTIVE: The C-reactive protein-albumin-lymphocyte (CALLY) index is a new index related to inflammation, immunity, and nutrition. We investigated whether it can predict the prognosis of patients with non-small cell lung cancer (NSCLC) and developed a prognostic model including CALLY index. RESEARCH METHODS AND PROCEDURES: Data from patients with NSCLC who were followed up in the INSCOC database from May 2013 to December 2018 were retrospectively analyzed. Simple random sampling by splitting these patients into training (n = 1307) and validation cohorts (n = 557) resulted in a sample size ratio of 7:3. Using the results of COX regression analysis of the training cohort, a nomogram model for predicting 3- and 5-year overall survival (OS) was established and validated internally. The calibration and clinical decision curve were used to evaluate the prediction accuracy and clinical application ability of the nomogram and compared with the TNM staging system for lung cancer. RESULTS: Sex, TNM stage, surgical treatment, BMI, CALLY, and HGS were independent risk factors for the prognosis of NSCLC patients. The OS of NSCLC patients with a low CALLY index score was significantly worse than that of patients with a high CALLY index (P < 0.001). The CALLY-based nomogram had a good predictive prognostic power, with a C-index of 0.697. Compared with the traditional TNM staging system, our prognostic nomogram had better resolution and accuracy in predicting the 3-year and 5-year OS. Decision curve analysis showed that this prognostic model has a clinical application value. CONCLUSIONS: The CALLY index is a valuable biomarker for evaluating the prognosis of patients with lung cancer. The nomogram based on the CALLY index is highly effective in predicting OS in patients with NSCLC. The results of this study provide a reference tool for clinicians to guide the personalized treatment of patients with lung cancer.

Association between the Dietary Inflammatory Index and All-Cause Mortality in Adults with Obesity.

INTRODUCTION: The dietary inflammatory index (DII) is associated with numerous chronic noncommunicable diseases. Previous studies have shown that the pro-inflammatory DII categories are associated with abdominal and simple obesity. However, the association between DII and mortality in patients with abdominal obesity and simple overweight or obesity remains unclear. METHODS: We used data from the US National Health and Nutrition Examination Survey (NHANES) from 2007 to 2018. A DII >0 (positive DII) was defined as a pro-inflammatory diet. A restricted cubic spline curve was used to describe the trend between DII and all-cause mortality. We then examined the association between DII and all-cause mortality in different body types using a Cox regression analysis and investigated the differences between sexes. Finally, the mediating effects of systemic inflammation were explored. RESULTS: A pro-inflammatory diet increased all-cause mortality in adults with abdominal obesity (aHR: 1.31, 95% confidence interval [CI]: 1.11-1.54; p < 0.001) and with simple overweight or obesity (aHR: 1.30, 95% CI: 1.11-1.53; p < 0.001). In addition, the most pro-inflammatory DII increased the risk of mortality by 43% (hazard ratio [HR]: Q4 vs. Q1 = 1.43, 95% CI = 1.14-1.79; p = 0.002; p for trend = 0.003) and 39% (HR: Q4 vs. Q1 = 1.39, 95% CI = 1.13-1.74; p = 0.003; p for trend = 0.009) in participants with abdominal obesity and with simple overweight or obesity, respectively. However, this association was not present in normal-sized participants. Compared with men, women resisted the effects of a pro-inflammatory diet. Mediation analysis showed that white blood cell and neutrophil were mediators of the association between DII and all-cause mortality (p < 0.001). CONCLUSION: A pro-inflammatory diet is associated with all-cause mortality in adults with abdominal obesity and simple overweight or obesity, and this effect differs between men and women. Systemic inflammation may mediate the association between DII and all-cause mortality.

Prognostic significance of preoperative prognostic immune and nutritional index in patients with stage I-III colorectal cancer.

BACKGROUND: To explore the value of preoperative prognostic immune and nutritional index (PINI) in predicting postoperative complications and long-term outcomes in patients with stage I-III colorectal cancer (CRC). METHODS: Restricted cubic splines were used to assess the relationship between PINI and survival in patients with CRC. The Kaplan-Meier method and log-rank test were used to plot the survival curves. The Cox proportional hazards model was used to evaluate independent prognostic predictors in patients with CRC. A logistic regression analysis was performed to identify independent predictors of postoperative complications. The least absolute shrinkage and selection operator (LASSO) logistic regression algorithm was used for feature screening. RESULTS: An evident positive dose-response relationship between PINI and survival in patients with CRC was identified. Compared with patients with a high PINI, those with a low PINI had worse disease-free survival (DFS) (47.9% vs. 66.9%, p < 0.001) and overall survival (OS) (49.7% vs. 70.2%, p < 0.001). The Cox proportional hazards model revealed that PINI was independently associated with DFS (hazard ratio [HR], 0.823; 95% confidence interval [CI], 0.754-0.898; p < 0.001) and OS (HR, 0.833; 95% CI, 0.761-0.912; p < 0.001) in patients with CRC. In the logistic regression analysis, PINI was an independent factor affecting postoperative complications in patients with CRC (odds ratio, 0.710; 95%CI: 0.610-0.810, p < 0.001). The LASSO logistic regression algorithm was used to screen for effective prognostic variables. Finally, we constructed PINI-based nomograms to predict postoperative 1-5-year PFS, and OS in patients with CRC. CONCLUSION: PINI is an effective biomarker for predicting postoperative complications, DFS, and OS in patients with stage I-III CRC.

A novel inflammation-nutrition biomarker score for predicting prognosis of patients with cancer: results from a multicenter study.

BACKGROUND: This study aimed to develop an innovative inflammation-nutrition biomarker score (INS) system to stratify the prognoses of patients with cancer. METHODS: A total of 5,221 patients with cancer from multiple centers in China between June 2010 and December 2017 were enrolled in this prospective cohort study. We compared the commonly used inflammation and nutrition biomarkers and selected the most valuable to develop the novel INS system. Survival curves were assessed using the Kaplan-Meier method and the log-rank test to evaluate the difference in survival rates between groups. The Cox proportional hazards model was used to investigate the association between biomarkers and all-cause mortality. RESULTS: As the risk stratification of INS increased (1 to 5), the rate of death for cancer patients gradually increased (25.43% vs. 37.09% vs. 44.59% vs. 56.21% vs. 61.65%, p < 0.001). The INS system was associated with all-cause mortality in patients with cancer. Patients with both high inflammation and nutrition risk (INS = 5) were estimated to have much worse prognosis than those with neither (HR, 2.606; 95%CI, 2.261-3.003, p < 0.001). Subsequently, the results of randomized internal validation also confirmed that INS system had an ideal effect in identifying adverse outcomes. In addition, the INS system could be used as a supplement to pathological stages in prognosis assessment, and had a higher predictive value in comparison with the constitute biomarkers. Patients with a high INS had less functional ability, reduced quality of life, and were at high risk of malnutrition, cachexia, and poor short-term outcomes. CONCLUSION: The INS system based on inflammation and nutrition biomarkers is a simple and effective prognostic stratification tool for patients with cancer, which can provide a valuable reference for clinical prognosis assessment and treatment strategy formulation.

Prognostic importance of systemic inflammation and insulin resistance in patients with cancer: a prospective multicenter study.

BACKGROUND: Systemic inflammation and insulin resistance (IR) are often associated with poor prognosis in cancer. This study aimed to investigate the prognostic value of surrogate systemic inflammation and IR indices in patients with cancer. METHODS: This multicenter prospective study included 5,221 patients with cancer, with a mean age of 59.41±11.15 years, of whom 3,061 (58.6%) were male. The surrogate IR indices included low-density lipoprotein cholesterol to high-density lipoprotein cholesterol (LHR) ratio, total cholesterol to high-density lipoprotein cholesterol (TC/ HDL-c) ratio, triglyceride to high-density lipoprotein cholesterol (TG/HDL-c) ratio, and fasting triglyceride glucose (TyG). Prognostic receiver operator characteristic (ROC) curves and C-indices were used to select a better surrogate IR index in patients with cancer. The prognostic value of the indicators was evaluated using univariate and multivariate survival analyses. RESULTS: In this study, the median survival time of patients was 44.5 (40.5-51.4) months, and the overall mortality in the 12-month period was 1,115 (53.7%), with 196 mortality events per 1,000 patient-years of patients' follow-up. The prognostic ROC curve and C-index suggested that the prognostic value of LHR was better than that of the other IR indices. The multivariate-adjusted hazard ratios (HRs) for overall survival (OS) were higher in patients with high C-reactive protein (CRP) (HR, 1.51; 95% confidence interval [CI]: 1.38-1.65) and high LHR (HR, 1.20; 95% CI: 1.06-1.37), respectively. The mortality rate of patients with both high CRP and LHR was 1.75-fold higher than that of patients with both low CRP and LHR. CONCLUSION: Both CRP and LHR showed good survival predictions in patients with cancer. CRP combined with LHR can improve the predictive power of patients with cancer.

Lymphocyte to C-reactive protein ratio could better predict the prognosis of patients with stage IV cancer.

BACKGROUND: Systemic inflammation is currently regarded as a hallmark of cancer. This study aimed to accurately clarify the prognostic value of various inflammatory markers in patients with stage IV cancer. METHODS: This study assessed 2,424 patients with cancer diagnosed with cancer in tumor, node, metastasis (TNM) stage IV. After evaluating the predictive value of 13 inflammatory indicators for patient prognosis using the C index, the lymphocyte C-reactive protein ratio (LCR) was selected to elucidate the prognostic and predictive values in patients with stage IV cancer. Kaplan-Meier and Cox proportional hazards regression models were used to analyze long-term survival. RESULTS: A total of 1,457 men (60.1%) and 967 women (39.9%) diagnosed with TNM stage IV cancer were enrolled. A ratio of 2,814 was defined as the optimal cut-off value for the LCR. The LCR was the most accurate prognosis predictor for patients with stage IV cancer among the 13 inflammatory nutritional markers evaluated. The multivariate-adjusted restricted cubic spline plot suggested that LCR had an L-shaped dose-response association with all-cause mortality risk. Patients with lower LCR levels tended to present with worse prognoses. Kaplan-Meier curves and log-rank test results showed that the high LCR groups (LCR ≥ 2,814) exhibited a better prognosis, whereas patients with stage IV cancer of different sex and tumor types (for example, gastrointestinal tumor, non-gastrointestinal tumor, and lung cancer) had a worse survival time. CONCLUSION: The LCR score can be regarded as a stable and useful biomarker to predict prognosis in patients with TNM stage IV compared to other evaluated inflammation indicators.

Pretreatment Albumin-to-Fibrinogen Ratio is a Promising Biomarker for Predicting Postoperative Clinical Outcomes in Patients with Colorectal Cancer.

PURPOSE: To evaluate the prognostic value of pretreatment albumin-to-fibrinogen ratio (AFR) in colorectal cancer (CRC). METHODS: This retrospective study included 657 CRC patients who underwent surgical resection in 2012-2014. Kaplan-Meier survival curve and Cox proportional hazards model were used to determine independent predictors. Receiver operating characteristic curve analysis was used to assess and compare the ability of indicators to predict survival. RESULTS: The optimal cutoff value of AFR was 8.3. Compared with high AFR group, low AFR group had shorter progression-free survival (PFS) (65.32% vs 52.28%, p < 0.001) and overall survival (OS) (67.47% vs 56.14%, p = 0.001). In the stratified analysis of TNM stage, AFR had good prognostic discrimination for early- and advanced-stage patients. Multivariate analysis suggested that AFR was an independent prognostic factor of PFS [hazard ratio (HR) = 1.385, 95% confidence interval (CI) = 1.043-1.839, p = 0.024) and OS (HR = 1.342, 95% CI = 1.022-1.763, p = 0.034) for CRC patients. AFR had better prognostic prediction ability than other inflammation-related markers. The AFR-based nomograms had good predictive capabilities. CONCLUSIONS: Pretreatment AFR is an independent prognostic factor for CRC patients undergoing surgical resection and is superior to other established inflammation-related markers.

Comprehensive comparison of the prognostic value of systemic inflammation biomarkers for cancer cachexia: a multicenter prospective study.

AIMS: Systemic inflammation plays an important role in cancer cachexia. However, among the systemic inflammatory biomarkers, it is unclear which has optimal prognostic value for cancer cachexia. METHODS: The Kaplan-Meier method was used and the log-rank analysis was performed to estimate survival differences between groups. Cox proportional hazard regression analyses were conducted to assess independent risk factors for all-cause mortality. RESULTS: The C-reactive protein-to-albumin ratio (CAR) was the optimal prognostic assessment tool for patients with cancer cachexia, with 1-, 3-, and 5-year predictive powers of 0.650, 0.658, and 0.605, respectively. Patients with a high CAR had significantly lower survival rates than those with a low CAR. Moreover, CAR can differentiate the prognoses of patients with the same pathological stage. Cox proportional risk regression analyses showed that a high CAR was an independent risk factor for cancer cachexia. For every standard deviation increase in CAR, the risk of poor prognosis for patients with cancer cachexia was increased by 20% (hazard ratio = 1.200, 95% confidence interval = 1.132-1.273, P < 0.001). CONCLUSIONS: CAR is an effective representative of systemic inflammation and a powerful factor for predicting the life function and clinical outcome of patients with cancer cachexia.

Preoperative computed tomography-assessed sarcopenia as a predictor of complications and long-term prognosis in patients with colorectal cancer: a systematic review and meta-analysis.

BACKGROUND: The relationship between computed tomography (CT)-assessed sarcopenia and colorectal cancer (CRC) prognosis varies in different studies. This systematic review aimed to examine the impact of preoperative CT-assessed sarcopenia on complications and long-term survival in CRC patients. METHODS: The PubMed, Web of Science, Cochrane Library, and Embase databases were searched for relevant literature up to September 10, 2020. Data and characteristics for each study were extracted. Long-term outcomes were assessed using a comprehensive HR with a 95% CI. Complications were assessed using a comprehensive OR with 95% CI. The heterogeneity and publication bias were also investigated, and subgroup and sensitivity analyses were performed. RESULTS: A total of 19 studies comprising 15,889 patients were included. The comprehensive results demonstrated that sarcopenia is significantly associated with overall survival of CRC patients (HR = 1.40, 95% CI = 1.25-1.58, p < 0.001). Patients with sarcopenia have a higher risk of complications compared to those without sarcopenia. In addition, sarcopenia is strongly associated with poor cancer-specific survival (HR = 1.49, 95% CI = 1.32-1.68, p < 0.001) and disease-free survival (HR = 1.59, 95% CI = 1.32-1.92, p < 0.001) in CRC patients. There is no significant relationship between sarcopenia and recurrence-free survival (HR = 1.32, 95% CI = 0.92-1.89, p = 0.126). CONCLUSIONS: Preoperative CT-assessed sarcopenia can be employed as an effective predictor of complications and long-term prognosis in CRC patients. Standardization of CT-assessed sarcopenia requires comprehensive consideration of race, muscle mass index, body mass index, and gender.

Feature Selection Using Enhanced Particle Swarm Optimisation for Classification Models.

In this research, we propose two Particle Swarm Optimisation (PSO) variants to undertake feature selection tasks. The aim is to overcome two major shortcomings of the original PSO model, i.e., premature convergence and weak exploitation around the near optimal solutions. The first proposed PSO variant incorporates four key operations, including a modified PSO operation with rectified personal and global best signals, spiral search based local exploitation, Gaussian distribution-based swarm leader enhancement, and mirroring and mutation operations for worst solution improvement. The second proposed PSO model enhances the first one through four new strategies, i.e., an adaptive exemplar breeding mechanism incorporating multiple optimal signals, nonlinear function oriented search coefficients, exponential and scattering schemes for swarm leader, and worst solution enhancement, respectively. In comparison with a set of 15 classical and advanced search methods, the proposed models illustrate statistical superiority for discriminative feature selection for a total of 13 data sets.

The diagnosis and prognosis values of WNT mRNA expression in colon adenocarcinoma.

WNT family genes have participated in the progression and development of many cancers, however, the association between colon adenocarcinoma (COAD) and WNTs have been rarely reported. This study investigated the significance of WNT genes expression in COAD from the standpoint of diagnosis and prognosis. The RNA-sequencing dataset of COAD was downloaded from The Cancer Genome Atlas and University of California, Santa Cruz Xena browser. The biology functions of WNT genes were investigated by biological analysis. Biological analysis of WNT family genes indicated that WNT genes were noticeably enriched in the complex process of WNT signaling pathway. The Pearson correlation analysis suggested WNT1 and WNT9B had a strong correlation. And receiver operating characteristic curves suggested that most of the genes could serve as a significant diagnostic makers in COAD (P < .05), especially WNT2 and WNT7B had high diagnostic values that the area under curve were 0.997 (95% confidence interval [0.994-1.000]) and 0.961 (95%CI [0.939-0.983]), respectively. And our multivariate survival analysis suggested the downregulated of WNT10B (P < .05) showed a favor prognosis in COAD overall survival. And the risk score model predicted that the upregulated expression of WNT10B might increase the risk of death. The very study we had conducted suggested that WNT genes had a certain connection with the diagnosis and prognosis of COAD. The messenger RNA expression of WNT2 and WNT7B might become potentially diagnostic biomarkers, and WNT10B might serve as an independent prognosis indicator for COAD.

Geriatric nutritional risk index as a predictor of complications and long-term outcomes in patients with gastrointestinal malignancy: a systematic review and meta-analysis.

BACKGROUND: The effect of the geriatric nutritional risk index (GNRI) on the prognosis of patients with gastrointestinal malignancy remains unclear. The aim of our study was to systematically explore the value of the GNRI in evaluating postoperative complications and long-term outcomes in gastrointestinal malignancy. METHODS: A systematic literature search was conducted using electronic databases to report the impact of the GNRI on postoperative complications and long-term outcomes of patients with gastrointestinal malignancies as of August 2020. The hazard ratio (HR) with a 95% confidence interval (CI) was used to evaluate the impact of the GNRI on long-term outcomes. The risk ratio (RR) with 95% CI was used to assess the impact of the GNRI on postoperative complications. RESULT: A total of nine studies with 2,153 patients were enrolled in our meta-analysis. The results suggested that a low GNRI was correlated with poor overall survival of patients with gastrointestinal malignancy (HR = 1.94, 95% CI 1.65-2.28, p < 0.001). Patients with a low GNRI had a higher risk of complications than patients with a high GNRI (OR = 2.19, 95% CI 1.57-3.05, p < 0.001). In addition, patients with a low GNRI had shorter relapse-free survival (HR = 2.45, 95% CI 1.50-4.00, p < 0.001) and disease-free survival (HR = 1.84, 95% CI 1.23-2.76, p = 0.003) than those with a high GNRI. However, the GNRI was not an independent factor affecting cancer-specific survival (HR = 1.60, 95% CI 0.91-2.82, p = 0.101). CONCLUSION: Based on existing evidence, the GNRI was a valuable predictor of complications and long-term outcomes in patients with gastrointestinal malignancy.