Survival Time Of Patients Research Articles

Expression and prognostic significance of KAP1 gene in malignant pleural mesothelioma

Objective: To explore the expression of KAP1 (KRAB-associated protein 1, KAP1) in Malignant pleural mesothelioma (MPM) based on the cancer genome atlas (TCGA) and clinical trials. And elucidate the correlation between the expression of KAP1 and the clinical pathological parameters of patients with MPM and its prognosis. Methods: In April 2022, Based on the second generation KAP1mRNA sequencing data and clinicopathological data of MPM patients downloaded from TCGA database, the correlation between KAP1mRNA expression and clinical parameters was analyzed, and the correlation between KAP1 protein expression and clinicopathological parameters and its prognostic value were analyzed based on Chuxiong data set cohort clinical samples. The expression of KAP1 mRNA in MPM samples and matched normal tumor adjacent tissues was detected by qRT-PCR, and the expression of KAP1 protein in MPM and normal pleural tissues was detected by immunohistochemistry and Westernblotting. To construct a Kaplan-Meier model to explore the effect of KAP1 expression on the prognosis of MPM patients, and to analyze the prognostic factors of MPM patients by Cox regression. Results: qRT-PCR and Western blotting detection showed that the expression levels of KAP1 gene in four different MPM cells (NCI-H28, NCI-H2052, NCI-H2452, and MTSO-211H) were significantly higher than those in normal pleural mesothelial cells Met-5A. qRT-PCR, Western blotting and IHC results demonstrated that the mRNA and protein expression levels of KAP1 in MPM tissues was significantly higher than that in matching normal mesothelial tissues, and the expression level of KAP1 protein was correlated with TP 53 protein expression levels and serum CEA levels (P<0.05) . The mRNA expression level was significantly correlated with the prognosis, The overall survival time of mesothelioma patients with high KAP1mRNA expression was significantly shorter (HR=3.7, Logrank P<0.001) . Tumor type, age and the mRNA expression were related to the prognosis of MPM patients (P<0.05) . Multivariate analysis showed that tumor type and KAP1 mRNA expression level were independent prognostic factors of MPM patients (P<0.05) . Conclusion: In this study, TCGA database and Chuxiong cohort experiment samples were used to collect the relevant information of KAP1 expression in malignant melanoma tissues. It was confirmed that KAP1 is highly expressed in MPM tissues. The mRNA expression level and pathological type are correlated with the prognosis of patients.

The experiences of family resilience in patients with permanent colostomy and their spouses: A dyadic qualitative study

PurposeWith the prolonged survival time of patients with permanent colostomy for colorectal cancer, they and their spouses face tremendous pressure and development dilemmas that can easily lead to family adaptation crises. This qualitative study amid to explore the dyadic experiences of family resilience among Chinese patients with permanent colostomy and their spouses. MethodsA phenomenological research method was adopted. Semi-structured, in-depth, face-to-face interviews with 10 dyads of patients with permanent colostomy and their spouses were recruited through purposive sampling from a public tertiary hospital in China from March 2023 to July 2023.The Dyadic interview analysis and Colaizzi methods were used to analyze the interview data. ResultsThree themes and nine subthemes were developed. (1) family crisis and dichotomous coping with stress-family crisis and coping pressure caused by enterostomy; (2) Adjustment and adaptation within the family-Joint adjustment and adaptation within the couple's family; and (3) integration and utilization of multi-dimensional social external resources (micro-level, meso-level, and macro-level). ConclusionsCouples living with permanent colostomy often undergo a complex emotional journey, experiencing varied levels of individual stress as they navigate social interactions and daily activities, which can contribute to a decline in family adaptation. With the help of the perspective of family advantage, health practitioners should pay attention to the evaluation of individual factors and family environmental resources, to fully mobilize advantage resources and give effective interventions to improve the family and social adaptation level of patients and their spouses.

A risk model based on lncRNA-miRNA-mRNA gene signature for predicting prognosis of patients with bladder cancer.

We aimed to analyze lncRNAs, miRNAs, and mRNA expression profiles of bladder cancer (BC) patients, thereby establishing a gene signature-based risk model for predicting prognosis of patients with BC. We downloaded the expression data of lncRNAs, miRNAs and mRNA from The Cancer Genome Atlas (TCGA) as training cohort including 19 healthy control samples and 401 BC samples. The differentially expressed RNAs (DERs) were screened using limma package, and the competing endogenous RNAs (ceRNA) regulatory network was constructed and visualized by the cytoscape. Candidate DERs were screened to construct the risk score model and nomogram for predicting the overall survival (OS) time and prognosis of BC patients. The prognostic value was verified using a validation cohort in GSE13507. Based on 13 selected. lncRNAs, miRNAs and mRNA screened using L1-penalized algorithm, BC patients were classified into two groups: high-risk group (including 201 patients ) and low risk group (including 200 patients). The high-risk group's OS time ( hazard ratio [HR], 2.160; 95% CI, 1.586 to 2.942; P= 5.678e-07) was poorer than that of low-risk groups' (HR, 1.675; 95% CI, 1.037 to 2.713; P= 3.393 e-02) in the training cohort. The area under curve (AUC) for training and validation datasets were 0.852. Younger patients (age ⩽ 60 years) had an improved OS than the patients with advanced age (age > 60 years) (HR 1.033, 95% CI 1.017 to 1.049; p= 2.544E-05). We built a predictive model based on the TCGA cohort by using nomograms, including clinicopathological factors such as age, recurrence rate, and prognostic score. The risk model based on 13 DERs patterns could well predict the prognosis for patients with BC.

Analysis of the sodium pump subunit ATP1A3 in glioma patients: Potential value in prognostic prediction and immunotherapy

The ATP1A3 gene is associated with the development and progression of neurological diseases. However, the pathological function and therapeutic value of ATP1A3 in glioblastoma (GBM) remains unknown. In this study, we tried to explore the correlation between the ATP1A3 gene expression and immune features in GBM samples. We found that ATP1A3 gene expression levels showed significant negative correlation with immune checkpoints such as PD-L1, CTLA-4 and IDO1. Next, ATP1A3 gene expression levels showed significant negative correlation with the anti-cancer immune cell process, the immune score and stromal score. By grouping ATP1A3 expression levels, we found that that immunomodulator-related genes and tumor-associated immune cell effector gene expression levels were associated with lower ATP1A3 expression. In addition, immunotherapy prediction pathway activity and a majority of the anti-cancer immune cell process activity levels were also showed to be correlated with lower ATP1A3 gene expression. Further, nine prognostic factors were identified by prognostic analysis, and a GBM prognostic model (risk score) was established. We applied the model to the TCGA GBM training set sample and the GSE4412 validation set sample and found that patients in the high risk score subgroup had significantly shorter survival time, demonstrating the prognostic value and prognostic efficacy of the risk score. Furthermore, ATP1A3 overexpression has also been found to sensitize cancer cells to anti-PD-1 therapy. In conclusion, we showed that ATP1A3 is a highly promising treatment target in GBM and the risk score is an independent prognostic factor for cancer and can be used to help guide the prediction of survival time in patients with GBM.

Comprehensive characterization of somatic mutations associated with chimeric RNAs in human cancers.

Chimeric RNAs, which can arise from gene recombination at the DNA level or non-canonical splicing events at the RNA level, have been identified as important roles in human tumors. Dysregulated gene expression caused by somatic mutations and altered splicing patterns of oncogenes or tumor suppressor genes can contribute to the development of tumors. Therefore, investigating the formation mechanism of chimeric RNAs via somatic mutations is critical for understanding tumor pathogenesis. This project is the first to propose studying the association between somatic single nucleotide variants and chimeric RNAs, identifying around 2900 somatic SNVs affecting chimeric RNAs in pan-cancer level. The somatic SNVs on chimeric RNAs were commonly observed in various types of tumor tissues, providing a valuable resource for future study. Additionally, these SNVs show distinct tumor specificity, and those with high frequency had a significant impact on the survival time of patients with tumors. Further research revealed that somatic SNVs associated with chimeric RNA (chiR-SNVs) were typically found within 10 nt of the junction site of chimeric RNAs and had a particularly significant effect on chimeric RNAs from different chromosomes. The enrichment analysis revealed that chiR-SNVs were significantly overrepresented in oncogenes and genes related to RNA binding proteins involved in RNA splicing, which could imply that chiR-SNVs may disrupt the process of RNA splicing and induce the occurrence of chimeric RNAs. This study sheds light on the potential molecular interaction mechanism between somatic SNVs and chimeric RNAs, which opens up a new avenue for researching disease pathway and tumorigenesis development.

Monitoring Ongoing Clinical Trials Under Fractional Brownian Motion With Drift

The standard Brownian motion (Bm) with a linear drift is a convenient statistical structure for monitoring ongoing clinical trials in practice for more than four decades (Lan and DeMets). Under this model, the most current one-point statistic is sufficient. However, in our experience, the sponsor and the data monitoring committee often would like to make decision or recommendation based on the “trend” observed from the history of data, not just a one-point snapshot. In this article, we introduce and advance the fractional Brownian motion (fBm) with drift model to formally accommodate this need. The possible dependence and/or the nonlinear trend (e.g., piecewise linear drift with change-point) of observations in clinical trials may come from uncontrollable factors such as patient entry processes may have seasonal patterns over time, patient survival time may depend on the practices of clinical centers, physicians or censoring time (Lai et al.). The violations of the standard Bm and the need for the fBm are discussed with illustrative examples. The common methods including conditional power and sample size re-estimation used for monitoring clinical trials are derived and implemented in the Dynamic Data Monitoring (DDM) system for practitioners under the fBm.

Machine learning-based identification of a consensus immune-derived gene signature to improve head and neck squamous cell carcinoma therapy and outcome.

Head and neck squamous cell carcinoma (HNSCC), an extremely aggressive tumor, is often associated with poor outcomes. The standard anatomy-based tumor-node-metastasis staging system does not satisfy the requirements for screening treatment-sensitive patients. Thus, an ideal biomarker leading to precise screening and treatment of HNSCC is urgently needed. Ten machine learning algorithms-Lasso, Ridge, stepwise Cox, CoxBoost, elastic network (Enet), partial least squares regression for Cox (plsRcox), random survival forest (RSF), generalized boosted regression modelling (GBM), supervised principal components (SuperPC), and survival support vector machine (survival-SVM)-as well as 85 algorithm combinations were applied to construct and identify a consensus immune-derived gene signature (CIDGS). Based on the expression profiles of three cohorts comprising 719 patients with HNSCC, we identified 236 consensus prognostic genes, which were then filtered into a CIDGS, using the 10 machine learning algorithms and 85 algorithm combinations. The results of a study involving a training cohort, two testing cohorts, and a meta-cohort consistently demonstrated that CIDGS was capable of accurately predicting prognoses for HNSCC. Incorporation of several core clinical features and 51 previously reported signatures, enhanced the predictive capacity of the CIDGS to a level which was markedly superior to that of other signatures. Notably, patients with low CIDGS displayed fewer genomic alterations and higher immune cell infiltrate levels, as well as increased sensitivity to immunotherapy and other therapeutic agents, in addition to receiving better prognoses. The survival times of HNSCC patients with high CIDGS, in particular, were shorter. Moreover, CIDGS enabled accurate stratification of the response to immunotherapy and prognoses for bladder cancer. Niclosamide and ruxolitinib showed potential as therapeutic agents in HNSCC patients with high CIDGS. CIDGS may be used for stratifying risks as well as for predicting the outcome of patients with HNSCC in a clinical setting.

Profile of miRNAs in small extracellular vesicles released from glioblastoma cells treated by boron neutron capture therapy.

Boron neutron capture therapy (BNCT) is a tumor cell-selective particle-radiation therapy. In BNCT, administered p-boronophenylalanine (BPA) is selectively taken up by tumor cells, and the tumor is irradiated with thermal neutrons. High-LET α-particles and recoil 7Li, which have a path length of 5-9μm, are generated by the capture reaction between 10B and thermal neutrons and selectively kill tumor cells that have uptaken 10B. Although BNCT has prolonged the survival time of malignant glioma patients, recurrences are still to be resolved. miRNAs, that are encapsulated in small extracellular vesicles (sEVs) in body fluids and exist stably may serve critical role in recurrence. In this study, we comprehensively investigated microRNAs (miRNAs) in sEVs released from post-BNCT glioblastoma cells. Glioblastoma U87 MG cells were treated with 25 ppm of BPA in the culture media and irradiated with thermal neutrons. After irradiation, they were plated into dishes and cultured for 3 days in the 5% CO2 incubator. Then, sEVs released into the medium were collected by column chromatography, and miRNAs in sEVs were comprehensively investigated using microarrays. An increase in 20 individual miRNAs (ratio > 2) and a decrease in 2 individual miRNAs (ratio < 0.5) were detected in BNCT cells compared with non-irradiated cells. Among detected miRNAs, 20 miRNAs were associated with worse prognosis of glioma in Kaplan Meier Survival Analysis of overall survival in TCGA. These miRNA after BNCT may proceed tumors, modulate radiation resistance, or inhibit invasion and affect the prognosis of glioma.

Identifying the Preoperative Radiological Risk Features in Patients with Leptomeningeal Carcinomatosis Undergoing Cerebrospinal Fluid Drainage

Patients with leptomeningeal carcinomatosis (LMC) experience a poor prognosis and rapid progression, and cerebrospinal fluid drainage (CSFD) is used to manage intracranial hypertension and hydrocephalus in LMC patients. This study aims to describe a novel discovery of preoperative radiological features in patients who underwent CSFD for LMC. A retrospective review was conducted during the past 5 years of LMC patients with intracranial hypertension and hydrocephalus who underwent CSFD. We evaluated the patients' preoperative radiological features, clinical characteristics, and survival times. A total of 36 patients were included. Of the 36 patients, 34 underwent ventriculoperitoneal shunting, and 2 patients underwent only external ventricular drainage due to rapid progression. The median preoperative Karnofsky performance scale score was 40.0 (interquartile range [IQR], 20.0-40.0). The median survival time after surgery was 5 months (IQR, 0.00-10.43 months). Of the 36 patients, 24 (66.7%) had supratentorial cerebral edema before surgery, including 14 patients (38.9%) with features of disproportionately enlarged subarachnoid space hydrocephalus (DESH). Four patients (11.1%) exhibited cerebellar swelling and had a median survival time of 0.27 month (IQR, 0.00-0.56 month). Nine patients (25%) have enhancement lesions on the cerebellum. The survival curve analysis shows that patients with features of cerebellar enhancement have shorter survival times than other patients. Patients with DESH features have longer survival times compared with those with global cerebral edema. Patients with radiological features of cerebellar enhancement have shorter postoperative survival than other patients; however, those with supratentorial cerebral edema, especially features of DESH, could benefit from CSFD. Patients with cerebellar swelling should avoid undergoing CSFD.

Delivery of miR-29a improves the permeability of cisplatin by downregulating collagen I expression

In the clinical setting, chemotherapy is the most widely used antitumor treatment, however, chemotherapy resistance significantly limits its efficacy. Reduced drug influx is a key mechanism of chemoresistance, and inhibition of the complexity of the tumor microenvironment (TME) may improve chemotherapy drug influx and therapeutic efficiency. In the current study, we identified that the major extracellular matrix protein collagen I is more highly expressed in lung cancer tissues than adjacent tissues in patients with lung cancer. Furthermore, Kaplan–Meier analysis suggested that COL1A1 expression was negatively correlated with the survival time of patients with lung cancer. Our previous study demonstrated that miR-29a inhibited collagen I expression in lung fibroblasts. Here, we investigated the effect of miR-29a on collagen I expression and the cellular behavior of lung cancer cells. Our results suggest that transfection with miR-29a could prevent Lewis lung carcinoma (LLC) migration by downregulating collagen I expression, but did not affect the proliferation, apoptosis, and cell cycle of LLC cells. In a 3D tumoroid model, we demonstrated that miR-29a transfection significantly increased cisplatin (CDDP) permeation and CDDP-induced cell death. Furthermore, neutral lipid emulsion-based miR-29a delivery improved the therapeutic effect of cisplatin in an LLC spontaneous tumor model in vivo. In summary, this study shows that targeting collagen I expression in the TME contributes to chemotherapy drug influx and improves therapeutic efficacy in lung cancer.

Identification of Novel Molecular and Clinical Biomarkers of Survival in Glioblastoma Multiforme Patients: A Study Based on The Cancer Genome Atlas Data.

Glioblastoma multiforme (GBM) is the most prevalent type of brain tumour; although advancements in treatment have been made, the median survival time for GBM patients has persisted at 15 months. This study is aimed at investigating the genetic alterations and clinical features of GBM patients to find predictors of survival. GBM patients' methylation and gene expression data along with clinical information from TCGA were retrieved. The most overrepresented pathways were identified independently for each omics dataset. From the genes found in at least 30% of these pathways, one gene that was identified in both sets was further examined using the Kaplan-Meier method for survival analysis. Additionally, three groups of patients who started radio and chemotherapy at different times were identified, and the influence of these variations in treatment modality on patient survival was evaluated. Four pathways that seemed to negatively impact survival and two with the opposite effect were identified. The methylation status of PRKCB was highlighted as a potential novel biomarker for patient survival. The study also found that treatment with chemotherapy prior to radiotherapy can have a significant impact on patient survival, which could lead to improvements in clinical management and therapeutic approaches for GBM patients.

The Expression of METTL14 in Patients with Newly Diagnosed Acute Myeloid Leukemia and Its Clinical Significance

To detect the expression of RNA methyltransferase 14(METTL14) in bone marrow of patients with newly diagnosed acute myeloid leukemia (AML), and to investigate the clinical and prognostic significance of METTL14 expression in newly diagnosed AML. Bone marrow samples were collected from 100 patients with newly diagnosed AML as observation group and 60 patients with iron deficiency anemia AML as control group. And collected the clinical data of the AML patients. Real-time quantitative PCR (qRT-PCR) was used to detect the expression level of METTL14 in AML and IDA patients. The relationship between the expression level of METTL14 and clinicopathological features, prognosis was analyzed. Kaplan-Meier curves were used to analyze the effect of METTL14 on overall survival (OS) in AML patients. Cox risk regression model was used to analyze the prognostic factors affecting in patients with AML. Compared with the control group, the expression of METTL14 was significantly increased in AML patients (P < 0.05). Compared with the METTL14 low-expression group, patients in the METTL14 high-expression group had advanced age, high bone marrow cell number, poor efficacyand poor prognosis(P < 0.05). The overall survival time of patients with the METTL14 high-expression group was significantly shorter than that of the low-expression group (P < 0.05). The high expression of METTL14 was an independent risk factor for poor prognosis in AML. METTL14 is significantly overexpressed in AML patients, and its correlated with poor clinicopathological features and poor prognosis. It can be used as a prognostic marker and potential therapeutie target for AML patients.

Repeat Resection for Recurrent Glioblastoma in the WHO 2021 Era: A Prospective Matched Case-Control Study

INTRODUCTION: The role of resection for recurrent glioblastoma remains unclear. METHODS: Patients who underwent repeat resection for recurrent IDH-wild-type glioblastoma were prospectively matched with 1:1 control cohort (n = 30:30). The two groups signed the consent and were matched for age, gender, comorbidities, eloquent vs. non-eloquent location, preoperative tumor volume and extent of resection in first surgery, neuropathological features as in WHO 2021 classification, time to progression, tumor volume at the time of recurrence, Park Score, ventricular wall involvement, use of steroids or multiple antiseizure medications and adjuvant therapy. Primary aim was to evaluate the overall survival in two cohorts. The secondary aim was to determine predictive factors for long term survival after repeat resection. RESULTS: After matching, patients had a long term follow up until death. Median overall survival times for patients who underwent repeat and one resection was 23.8 months vs 9.1 months, respectively (Log-Rank p &lt; 0.001). Two predictive factors for long term survival after repeat resection were preoperative Karnofsky Performance Score &gt;70 and Glasgow Coma Scale &gt;13 (Fisher p = 0.07 and p &lt; 0.001, respectively) while age, time to surgery, preoperative volume, extend of resection in repeat resection, location of tumor, its extension to ventricular wall, ependymal enhancement, comorbidities, tumor histological and molecular features did not correlate with postoperative survival. CONCLUSIONS: This is the first prospective matched case-control study revealing survival benefit of repeat resection for recurrent gliomas with long term follow up in a select group.

Comprehensive analysis of CYBB as a prognostic marker and therapeutic target in glioma: A bioinformatics approach

BackgroundIn the central nervous system, glioma is the most common malignant tumor, and patients have a poor prognosis. Identification of novel marker genes and establishment of prognostic models are important for early diagnosis and prognosis determination. MethodsDownload glioma data from the CGGA and TCG databases. Application of bioinformatics to analyze the impact of CYBB on the clinicopathological characteristics, immunological features and prognosis of gliomas. Using single-cell sequencing data from 7 glioblastoma patients in the CGGA database, the role of CYBB in the tumor microenvironment was analyzed. In addition, a prognostic model was constructed based on CYBB high and low differentially expressed genes and mitochondrial genes. ResultsThe expression of CYBB is closely related to various clinical features, immune cell infiltration level, immune checkpoint and survival time of patients. A 10-gene prediction model was constructed based on the differentially expressed genes of low and high CYBB and mitochondria-related genes. Glioma patients with higher risk scores had significantly lower survival probabilities. Receiver operating characteristic curves and nomograms were plotted over time to show the predictive accuracy and predictive value of the 10-gene prognostic model. ConclusionsOur study shows that CYBB is strongly correlated with clinical characteristics features and prognosis of glioma patients, and can be used as a potential therapeutic target. Prognostic models based on CYBB and mitochondrial genes have good performance in predicting prognosis of glioma patients.

Effects of BMAL2 on Aerobic Glycolysis and Cell Proliferation in Acute Myeloid Leukemia Cells

To explore the expression of basic helix-loop-helix ARNT like 2 (BMAL2) in acute myeloid leukemia (AML) patients and its correlation with prognosis, and analyze its effects on the aerobic glycolysis and proliferation of AML cells. The expressions of BMAL2 in bone marrow mononuclear cells (BMMCs) of AML patients and normal control group were detected by RT-qPCR. The correlation of BMAL2 expression with prognosis of AML patients was analyzed using public database of National Center for Biotechnology Information (NCBI). The interfering in BMAL2 expression of HL-60 and Kasumi-1 cells was performed using lentiviral vector-mediated shRNA. Cell glucose metabolism and proliferation were detected by using glucose uptake experiment, lactate content test, CCK-8 assay and cell colony formation test. The expression level of BMAL2 mRNA in BMMCs of AML patients was significantly higher than normal control group (P < 0.01). The overall survival time of AML patients with high expression of BMAL2 was significantly shorter than those with low expression of BMAL2 (P < 0.05). Knockdown of BMAL2 significantly reduced glucose uptake and lactate production in AML cell line HL-60 and Kasumi-1 cells. The results of RT-PCR and Western blot showed that BMAL2 promoted aerobic glycolysis by enhancing the expression of HIF1A in AML cells, thereby promoting cell proliferation. BMAL2 is highly expressed in AML patients, and promotes aerobic glycolysis by enhancing the expression of HIF1A, thereby promoting cell proliferation.

CT-based radiomics and clinical characteristics for predicting bone metastasis in lung adenocarcinoma patients.

The occurrence of bone metastasis (BM) will seriously shorten the survival time of lung adenocarcinoma patients and aggravate the suffering of patients. Computed tomography (CT)-based clinical radiomics nomogram may help clinicians stratify the risk of BM in lung adenocarcinoma patients, thereby enabling personalized individualized clinical decision making. A total of 501 patients with lung adenocarcinoma from March 2017 to March 2019 were enrolled in the study. Based on plain chest CT images, 1130 radiomics features were extracted from each lesion. One-way analysis of variance (ANOVA) and least absolute shrinkage selection operator (LASSO) algorithm were used for radiomics features selection. Univariate and multivariate analyses were used to screen for clinical characteristics and identify independent predictors of BM. Three models (radiomics model, clinical model and combined model) were constructed to predict BM in lung adenocarcinoma patients. Receiver operating characteristic (ROC) curve and decision curve analysis (DCA) were used to evaluate the performance of the three models. The DeLong test was used to compare the performance of the models. Finally, the clinical model for predicting BM in lung adenocarcinoma patients was constructed based on 5 independent predictors: cytokeratin 19-fragments (CYFRA21-1), stage, Ki-67, edge, and lobulation. The radiomics model was constructed based on 5 radiomics features. The combined model incorporating clinical independent predictors and radiomics was constructed. In the validation cohort, the area under the curve (AUC) of the clinical model, radiomics model and combined model was 0.824, 0.842 and 0.866, respectively. Delong test showed that in the training cohort, the AUC values of the radiomics model and the combined model were statistically different (P=0.03), and the AUC values of the other models were not statistically different. DCA showed that the nomogram had a highest net clinical benefit. The CT-based clinical radiomics nomogram can be used as a non-invasive and quantitative method to help clinicians stratify the risk of BM in patients with lung adenocarcinoma, thereby enabling personalized clinical decision making.

The impact of modified T3 sub-staging on the prognosis of gallbladder cancer patients

Objective: To explore the value of a new modified T3 sub-staging for the prognosis evaluation in gallbladder cancer patients. Methods: This is a retrospective case-series study. The clinical data of patients with pathologically confirmed stage T3 gallbladder cancer who were admitted to the Department of Hepatobiliary Surgery,the First Affiliated Hospital of Xi'an Jiaotong University from January 2011 to December 2021 were retrospectively analyzed. A total of 190 patients were enrolled in this study, 67 males and 123 females, with an age (M(IQR)) of 63(14) years (range:17 to 88 years). The stage T3 was divided into four sub-stages according to the site of tumor invasion: (1) T3a:tumor perforates the serosa,but not invading the liver and one other adjacent structure; (2) T3b:tumor perforates the serosa and invades one other adjacent structure,but not the liver; (3) T3c:tumor perforates the serosa and invades the liver,but not one other adjacent structure; (4) T3d:tumor perforates the serosa,invades the liver and one other adjacent structure. To evaluate the application value of this modified sub-staging,the Kaplan-Meier method was used to draw the survival curve,univariate analysis and multivariate analysis were done using the Log-rank test and Cox proportional hazard model respectively. Results: According to the modified T3 sub-staging method,34 patients (17.9%) were in stage T3a,24 cases(12.6%) were in stage T3b, 97 cases (51.1%) were in stage T3c, and 35 cases (18.4%) were in stage T3d. The median survival time of patients in stages T3a,T3b,T3c and T3d after radical resection was 72.0 months, 32.0 months, 12.0 months and 10.0 months, respectively. The 1-, 3-, and 5-year survival rates of patients in stage T3a, T3b, T3c and T3d were 79.4%, 53.3%, and 53.3%; 79.2%, 44.6%, and 26.0%;49.5%,27.5%,and 18.1%;42.9%,15.9%, and 15.9% (χ2=18.349,P<0.01),respectively. Univariate analysis showed that gallbladder stones,pathological differentiation,perineural invasion, N stage,postoperative adjuvant therapy and modified T3 substage were factors affecting patient prognosis(all P<0.05). Cox multivariate analysis showed that modified sub-stages with T3c (HR=2.043, 95%CI:1.176 to 3.549) and T3d(HR=2.419, 95%CI:1.284 to 4.555), accompanied by gallbladder stones (HR=1.661,95%CI:1.150 to 2.398),pathological differentiation with poorly differentiated(HR=1.709,95%CI:1.198 to 2.438), and the N stage with N1 and N2(HR=1.602, 95%CI:1.090 to 2.355, 2.714, 95%CI: 1.621 to 4.544) were independent prognostic risk factors for patients in stage T3,while postoperative adjuvant chemotherapy(HR=0.351) was a protective factor for prognosis. There was no statistically significant difference in survival between patients with stage T3a and T3b who underwent hepatic wedge resection and liver segment or major resection (P=0.402). For patients with stage T3c and T3d with liver invasion,the survival difference after hepatic wedge resection and segmental or major resection was statistically significant (P=0.008). Conclusion: The modified T3 sub-staging system based on the depth and direction of tumor invasion maybe helpful to further stratify the prognosis of patients with gallbladder cancer.

Negative Impact of Intra-Operative Blood Transfusion on Survival Outcomes of Hepatocellular Carcinoma Patients.

Studies have reported that blood transfusion may have an association with survival outcomes of cancer patients. This study was aimed at finding the effect of intra-operative blood transfusion on the prognosis of patients of hepatocellular carcinoma (HCC). This was a retrospective study. HCC patients who underwent tumor resection from January 2013 to November 2018 at Harbin Medical University Cancer Hospital were included. The survival time of patients receiving or not receiving blood transfusion during the operation were compared. Of HCC patients, 21.1% (102/484) received intra-operative blood transfusion. After propensity score matching, 87 pairs of patients were included in the study. In the subset of patients with a tumor size of >4 cm, univariable analysis found that there were significant differences in recurrence-free survival (RFS; P=0.004) and overall survival (OS; P=0.028) between blood transfusion and non-blood transfusion groups. After multivariable Cox regression analysis, intra-operative blood transfusion was an independent risk factor for RFS (HR: 2.011, 95% CI: 1.146-3.529, P=0.015), but not for OS (HR: 1.862, 95% CI: 0.933-3.715, P=0.078) in the subset of patients with a tumor size of >4 cm. Intra-operative blood transfusion was associated with worse RFS in HCC patients with a tumor size of >4 cm.

High MCM6 expression promotes proliferation and correlates with poor prognosis in triple-negative breast cancer.

Triple-negative breast cancer (TNBC) is an aggressive subtype with a poor prognosis. Minichromosome maintenance genes (MCM2-7) crucial for DNA replication are significant biomarkers for various tumor types; however, their roles in TNBC remain underexplored. We utilized four TNBC-related GEO databases to examine MCM2-7 gene expression and predict its prognosis in TNBC, performing single-cell analysis and GSEA to discover MCM6's potential function. The Cancer Dependency Map gene effect scores and CCK8 assay were used to assess MCM6's impact on TNBC cell proliferation. The correlations between MCM6 expression, immune infiltrates, and immune cells were also analyzed. WGCNA and LASSO Cox regression built a risk score model predicting TNBC patient survival based on MCM6-related gene expression. MCM2-7 gene expression was higher in TNBC tissues compared to adjacent normal tissues. High MCM6 expression correlated with shorter TNBC patient survival time. GSEA and single-cell analysis revealed a relationship between elevated MCM6 expression and the cell cycle pathway. MCM6 knockdown inhibited TNBC cell proliferation. A risk model featuring MCM6, CDC23, and CCNB1 effectively predicts TNBC patient survival. MCM6 overexpression in TNBC links to a worse prognosis and reduced cell proliferation upon MCM6 knockdown. We developed a risk score model based on MCM6-related genes predicting TNBC patient prognosis, potentially assisting future treatment strategies.

Survivability Prediction of Breast Cancer Patients Using Three Data Mining Methods: A Comparative Study

Background and aims: Breast cancer (BC) is the leading cause of mortality among women. Early diagnosis is crucial for effective treatment. This study applied suitable data mining methods that provide rules and present influential prognostic factors on the survival time of BC patients. Methods: The dataset consisted of 1574 women diagnosed between January 2002 and December 2012 at the Cancer Registry Center of Nemazi hospital in Fars Province, Iran. Patients were classified based on prognostic factors using three popular data mining methods, including decision tree (J48), Naïve Bayes (NB), and nominal logistic regression (NLR). The Weka software was considered to compare these methods using sensitivity, specificity, and accuracy metrics. The outcome of the study was the median survival time, which was categorized into three classes. Results: In total, 212 women (13.5%) died of BC, whose mean age was 49.74 years old. Overall survival rates at 2, 3, 5, and 10 years were 0.98, 0.94, 0.87, and 0.76, respectively. The mean and median survival times were 4.81 and 4.27 years. Sensitivity, specificity, and accuracy for J48 and NB were 0.480, 0.570, and 0.572, as well as 0.483, 0.610, and 0.584, respectively. In addition, the corresponding values were 0.488, 0.584, and 0.579 for NLR, respectively. Further, J48 showed that the Nottingham Prognostic Index (NPI) was the most influential prognostic factor. Conclusion: This paper sought to improve the accuracy of BC classification using data mining methods. Comparing multiple prediction models gave us an insight into the relative prediction abilities of different data mining methods. The results suggested NB as the best classifier due to its higher accuracy and specificity. Finally, J48 identified the NPI as the most effective prognostic factor.