CDK1, CCNB1, and CCNB2 are Prognostic Biomarkers and Correlated with Immune Infiltration in Hepatocellular Carcinoma.

BACKGROUND Orderly G2/M transition in the cell cycle is controlled by the cyclin-dependent kinase 1/cyclin B (CDK1/CCNB) complex. We aimed to comprehensively investigate the roles of CDK1, CCNB1, and CCNB2 via multi-omics analysis and their relationships with immune infiltration in hepatocellular carcinoma (HCC). MATERIAL AND METHODS The transcriptional data and the epigenetic and genetic alterations of CDK1, CCNB1, and CCNB2, as well as their impacts on prognosis in HCC patients, were identified using multiple databases. The correlations between expression of these genes and immune infiltration in HCC were then explored using the TIMER database. RESULTS Overall, mRNA expression of CDK1, CCNB1, and CCNB2 was up-regulated in various tumor tissues including HCC. Higher expression of these genes was associated with poorer prognosis in HCC patients. Lower promoter methylation of these genes might cause higher expression levels in tumor tissues of HCC. Genetic alterations and several methylated-CpG sites in these genes were significantly associated with survival. Notably, expression levels of CDK1, CCNB1, and CCNB2 were positively correlated with infiltrating levels of CD4⁺ T cells, CD8⁺ T cells, neutrophils, macrophages, and dendritic cells in HCC. In addition, significant correlations between the expression of these genes and various immune markers in HCC, such as PD-1, PDL-1, and CTLA-4, were also observed. CONCLUSIONS CDK1, CCNB1, and CCNB2 are potential prognostic biomarkers and associated with immune cell infiltration in HCC. The genes may be utilized to predict the reaction of immunotherapy. Combining inhibitors of these genes with immunotherapy may improve the survival time of HCC patients.

FLNB overexpression promotes tumor progression and associates with immune suppression, evasion and stemness in pancreatic cancer.

Pancreatic cancer (PC) is an immunosuppressive cancer. Immune-based therapies that enhance or recruit antitumor immune cells into the tumor microenvironment (TME) remain promising strategies for PC treatment. Consequently, a deeper understanding of the molecular mechanisms involved in PC immune suppression is critical for developing immune-based therapies to improve survival rates. In this study, weighted gene co-expression network analysis (WGCNA) was used to identify Filamin B (FLNB) correlated with the infiltration of CD8+ T cells and tumor-associated macrophages (TAMs). The clinical significance and potential biological function of FLNB were evaluated using bioinformatic analysis. The oncogenic role of FLNB in PC was determined using in vitro and in vivo studies. We further analyzed possible associations between FLNB expression and tumor immunity using CIBERSORT, single sample gene set enrichment analysis, and ESTIMATE algorithms. We found FLNB was overexpressed in PC tissues and was correlated with poorer overall survival, tumor recurrence, larger tumor size, and higher histologic grade. Moreover, FLNB overexpression was associated with the mutation status and expression of driver genes, especially for KRAS and SMAD4. Functional enrichment analysis identified the role of FLNB in the regulation of cell cycle, focal adhesion, vascular formation, and immune regulation. Knockdown of FLNB expression inhibited cancer cell proliferation and migration in-vitro and suppressed tumor growth in-vivo. Furthermore, FLNB overexpression caused high infiltration of Treg cells, Th2 cells, and TAMs, but reduced infiltration of CD8+ T cells and Th1/Th2. Collectively, our findings suggest FLNB promotes PC progression and may be a novel biomarker for PC.

Prognostic significance of glucose-lipid metabolic index in pancreatic cancer patients with diabetes mellitus.

BACKGROUND: The incidence of pancreatic cancer (PC) is higher in diabetic patients due to disturbances in glucose and lipid metabolism caused by insulin resistance (IR). However, the effect of diabetes as well as IR on the prognosis of PC patients remains inconclusive. Our study aims to assess the impact of IR on the prognosis of PC patients with diabetes. METHODS: We conducted a retrospective analysis of 172 PC patients with diabetes in our institute from 2015 to 2021. Prognostic assessment was performed using univariate/multifactorial analysis and survival analysis. The predictive efficacy of metabolic indices was compared using receiver operator characteristic (ROC) curve analysis. RESULTS: One hundred twenty-one of 172 patients died during follow-up, with a median follow-up of 477 days and a median overall survival (OS) of 270 days. Survival analysis showed a significant difference in OS by IR related parameters, which were triglyceride-glucose index (TyG), triglyceride-glucose index-body mass index (TyG-BMI), and triglyceride/high-density lipoprotein cholesterol ratio (TG/HDL-c). The ROC curve indicated that TyG, TyG-BMI, and TG/HDL-c had prognostic efficacy for PC with diabetes. We next optimized TyG-BMI and obtained a new parameter, namely glucose-lipid metabolism index (GLMI), and the patients were classified into GLMI low group and high group based on the calculated cutoff value. The GLMI high group had higher TyG, TyG-BMI, TyG/HDL-c, BMI, TG, total cholesterol (TC), TC/HDL-c, fasting plasma glucose, CA199, and more advanced tumor stage compared to low group. Univariate and multivariate analyses showed that GLMI was an independent prognostic factor. Furthermore, the patients of GLMI high group had worse OS compared to low group and the ROC curves showed GLMI had better predictive ability than TyG and TyG-BMI. CONCLUSIONS: IR is associated with the outcome of PC patients with diabetes and higher level of IR indicates worse prognosis. GLMI has a good predictive value for PC with diabetes.

Identification and validation of stemness-based and ferroptosis-related molecular clusters in pancreatic ductal adenocarcinoma.

Pancreatic ductal adenocarcinoma (PDAC) is a highly lethal malignancy with an extremely poor prognosis. Cancer stem cells (CSCs) are considered to be responsible for the poor survival, recurrence and therapy resistance of PDAC. Ferroptosis plays a crucial role in the sustain and survival of CSCs. Here, we employed a rigorous evaluation of multiple datasets to identify a novel stemness-based and ferroptosis-related genes (SFRGs) signature to access the potential prognostic application. This work we retrieved RNA-sequencing and clinical annotation data from the TCGA, ICGC, GTEx and GEO database, and acquired 26 stem cell gene sets and 259 ferroptosis genes from StemChecker database and FerrDb database, respectively. Based on consensus clustering and ssGSEA analysis, we identified two expression patterns of CSCs traits (C1 and C2). Then, WGCNA analysis was implemented to screen out hub module genes correlated with stemness. Furthermore, differential expression analysis, Pearson correlation analysis, and the Least absolute shrinkage and selection operator (LASSO) and Cox regression were performed to identify the SFRGs and to construct model. In addition, the differences in prognosis, tumor microenvironment (TME) components and therapy responses were evaluated between two risk groups. Finally, we verified the most influential marker ARNTL2 experimentally by western blot, qRT-PCR, sphere formation assay, mitoscreen assay, intracellular iron concentration determination and MDA determination assays. In conclusion, we developed a stemness-based and ferroptosis-related prognostic model, which could help predict overall survival for PDAC patients. Targeting ferroptosis may be a promising therapeutic strategy to inhibit PDAC progression by suppressing CSCs.

Regulation of iron metabolism and ferroptosis in cancer stem cells.

The ability of cancer stem cells (CSCs) to self-renew, differentiate, and generate new tumors is a significant contributor to drug resistance, relapse, and metastasis. Therefore, the targeting of CSCs for treatment is particularly important. Recent studies have demonstrated that CSCs are more susceptible to ferroptosis than non-CSCs, indicating that this could be an effective strategy for treating tumors. Ferroptosis is a type of programmed cell death that results from the accumulation of lipid peroxides caused by intracellular iron-mediated processes. CSCs exhibit different molecular characteristics related to iron and lipid metabolism. This study reviews the alterations in iron metabolism, lipid peroxidation, and lipid peroxide scavenging in CSCs, their impact on ferroptosis, and the regulatory mechanisms underlying iron metabolism and ferroptosis. Potential treatment strategies and novel compounds targeting CSC by inducing ferroptosis are also discussed.

Genome-wide CRISPR/Cas9 screening for drug resistance in tumors.

Genome-wide clustered regularly interspaced short palindromic repeats (CRISPR)/CRISPR associated nuclease 9 (Cas9) screening is a simple screening method for locating loci under specific conditions, and it has been utilized in tumor drug resistance research for finding potential drug resistance-associated genes. This screening strategy has significant implications for further treatment of malignancies with acquired drug resistance. In recent years, studies involving genome-wide CRISPR/Cas9 screening have gradually increased. Here we review the recent application of genome-wide CRISPR/Cas9 screening for drug resistance, involving mitogen-activated protein kinase (MAPK) pathway inhibitors, poly (ADP-ribose) polymerase inhibitors (PARPi), alkylating agents, mitotic inhibitors, antimetabolites, immune checkpoint inhibitors (ICIs), and cyclin-dependent kinase inhibitors (CDKI). We summarize drug resistance pathways such as the KEAP1/Nrf2 pathway MAPK pathway, and NF-κB pathway. Also, we analyze the limitations and conditions for the application of genome-wide CRISPR/Cas9 screening techniques.

Risk Signature Related to Immunotherapy Reaction of Hepatocellular Carcinoma Based on the Immune-Related Genes Associated With CD8+ T Cell Infiltration.

Background: Hepatocellular carcinoma (HCC) is the most common histological type of liver cancer, with an unsatisfactory long-term survival rate. Despite immune checkpoint inhibitors for HCC have got glories in recent clinical trials, the relatively low response rate is still a thorny problem. Therefore, there is an urgent need to screen biomarkers of HCC to predict the prognosis and efficacy of immunotherapy. Methods: Gene expression profiles of HCC were retrieved from TCGA, GEO, and ICGC databases while the immune-related genes (IRGs) were retrieved from the ImmPort database. CIBERSORT and WGCNA algorithms were combined to identify the gene module most related to CD8+ T cells in the GEO cohort. Subsequently, the genes in hub modules were subjected to univariate, LASSO, and multivariate Cox regression analyses in the TCGA cohort to develop a risk signature. Afterward, the accuracy of the risk signature was validated by the ICGC cohort, and its relationships with CD8+ T cell infiltration and PDL1 expression were explored. Results: Nine IRGs were finally incorporated into a risk signature. Patients in the high-risk group had a poorer prognosis than those in the low-risk group. Confirmed by TCGA and ICGC cohorts, the risk signature possessed a relatively high accuracy. Additionally, the risk signature was demonstrated as an independent prognostic factor and closely related to the CD8+ T cell infiltration and PDL1 expression. Conclusion: A risk signature was constructed to predict the prognosis of HCC patients and detect patients who may have a higher positive response rate to immune checkpoint inhibitors.

Score for predicting overall survival in pancreatic adenocarcinoma patients with positive lymph nodes after surgery: a novel nomogram-based risk assessment.

BACKGROUND: Pancreatic adenocarcinoma (PaC) patients with positive lymph nodes (PLNs) have a dismal prognosis and lack a specific prognostic stage. This study aimed to construct a nomogram for the prediction of overall survival (OS) in these patients. METHODS: A total of 1,340 patients screened from the Surveillance, Epidemiology, and End Results database were included and randomly divided at a ratio of 7:3 into a training set (n=940) and an internal validation set (n=400). Cox regression analyses were conducted to select independent predictors in the training set, and a nomogram was constructed. The model was verified in the internal validation set and in an external validation set, which comprised 64 patients from a Chinese institute. RESULTS: Six independent prognostic factors (age at diagnosis, tumor grade, lymph node ratio, T stage, radiotherapy, and chemotherapy) were identified in PaC patients with PLNs and were entered into the nomogram. The final model had a higher C-index for predicting OS than the American Joint Committee on Cancer-8th edition staging system (training set: 0.658 vs. 0.546; internal validation set: 0.661 vs. 0.546; external validation set: 0.691 vs. 0.581). The 1-, 2-, and 3-year area under the receiver operating characteristic curve values indicated better discrimination power for the established nomogram with respect to the prediction of OS in the training, internal validation, and external validation sets than for the American Joint Committee on Cancer-8th edition staging system. Furthermore, the nomogram performed well in both calibration and decision curve analyses (DCA) of clinical applicability. OS in PaC patients with PLNs was significantly distinguished among the three risk groups stratified according to the nomogram score (P<0.001). CONCLUSIONS: The well-calibrated nomogram was determined to be extremely efficient in predicting survival, and defining a high-risk population based on the nomogram score among PaC patients with PLNs after surgery.

The role of hyperthermic intraperitoneal chemotherapy in the treatment of spontaneously ruptured hepatocellular carcinoma: a pilot study.

BACKGROUND: Spontaneous tumor rupture is a distinctive disease pattern in patients with hepatocellular carcinoma (HCC). The application of hyperthermic intraperitoneal chemotherapy (HIPEC) in spontaneously ruptured hepatocellular carcinoma (srHCC) is debatable. Our study aimed to compare the long-term outcomes of srHCC vs. nrHCC and to test the role of postoperative HIPEC in patients with srHCC after hepatectomy. METHODS: From 2014 to 2018, PSM was performed to compare 57 patients who performed liver resection for srHCC and met the research criteria with 57 nrHCC patients selected from 446 consecutive patients. Then patients with srHCC were divided into two groups according to whether they underwent HIPEC after hepatectomy. RESULTS: After 1:1 PSM, the clinical characteristics of the patients with srHCC and nrHCC were comparable. In terms of long-term outcomes, the nrHCC group had significantly longer OS (P=0.026) and DFS (P<0.001) than the srHCC group. Of the 57 srHCC patients, the HIPEC group showed added complications compared to the non-HIPEC group, including an increased length of hospital stay and higher in-hospital costs. However, there were no significant differences in the metastatic patterns of these recurrent patients, and there was no statistically significant difference in DFS (P=0.28) or OS (P=0.56) between the two groups. CONCLUSIONS: The prognosis of ruptured HCC patients were worse than those of non-ruptured HCC patients. HIPEC may not be a robust treatment for srHCC now.

YTHDF2 promotes the liver cancer stem cell phenotype and cancer metastasis by regulating OCT4 expression via m6A RNA methylation.

N6-methyladenosine (m6A) RNA methylation contributes to the cancer stem cell (CSC) phenotype through regulating gene expression. YTHDF2, an m6A reader, was shown to be associated with hepatocellular carcinoma (HCC) patient prognosis. However, the effect of YTHDF2 on liver CSC and cancer metastasis and the molecular mechanism of this effect have not been documented. Here, we show that YTHDF2 expression is negatively correlated with HCC patient survival in both data from the Cancer Genome Atlas (TCGA) database and clinical data from our center. By detecting CD133+ cells and carrying out sphere culture assays, we found that knockdown of YTHDF2 led to impaired stemness in Hep3B and Huh7 cells. In contrast, overexpression of YTHDF2 increased the CSC phenotype. Mechanistically, the knockdown and overexpression of YTHDF2 in liver cancer cells resulted in decreased and increased m6A levels in the 5'-untranslated region (UTR) of OCT4 mRNA, respectively, leading to decreased and increased OCT4 protein expression, respectively. A luciferase activity assay showed that mutation of the corresponding m6A methylation sequence in the 5'-UTR of OCT4 mRNA caused significantly decreased gene expression, suggesting a role for YTHDF2-dependent m6A methylation in protein translation. Polysome profiling results also indicated the knockdown and overexpression of YTHDF2 could decrease and increase OCT4 translation, respectively. In particular, overexpression of OCT4 rescued the impaired stemness caused by YTHDF2 depletion, which confirmed the effect of YTHDF2 on CSC phenotype is dependent on OCT4. In vivo, the loss of YTHDF2 reduced tumor burden and inhibited lung metastasis following orthotopic transplantation in nude mice. Last, we demonstrated that YTHDF2 expression is positively correlated with OCT4 expression and m6A levels in the 5'-UTR of OCT4 mRNA in clinical HCC specimens. In conclusion, YTHDF2 promotes the CSC liver phenotype and cancer metastasis by modulating the m6A methylation of OCT4 mRNA.

The role of intraoperative radiation therapy in resectable pancreatic cancer: a systematic review and meta-analysis.

PURPOSE: Several studies investigating the role of intraoperative radiotherapy (IORT) in the treatment of resectable pancreatic cancer (PC) have been published; however, their results remain inconsistent. By conducting a systematic review and meta-analysis, this study aimed to compare clinical outcomes in patients with resectable PC who underwent surgery with or without IORT. METHODS AND MATERIALS: The MEDLINE/PubMed, EMBASE, and Cochrane Library databases were searched to identify relevant studies published up to February 28, 2019. The main outcome measures included median survival time (MST), local recurrence (LR), postoperative complications, and operation-related mortality. Pooled effect estimates were obtained by performing a random-effects meta-analysis. RESULTS: A total of 1095 studies were screened for inclusion, of which 15 studies with 834 patients were included in the meta-analysis. Overall, 401 patients underwent pancreatic resection with IORT and 433 underwent surgery without IORT. The pooled analysis revealed that IORT group experienced favorable overall survival (median survival rate [MSR], 1.20; 95% confidence interval [CI], 1.06-1.37, P = 0.005), compared with patients who did not receive IORT. Additionally, the pooled data showed a significantly reduced LR rate in the IORT group compared with that in the non-IORT group (relative risk [RR], 0.70; 95% CI, 0.51-0.97, P = 0.03). The incidences of postoperative complications (RR, 0.95; 95% CI, 0.73-1.23) and operation-related mortality (RR, 1.07; 95% CI, 0.44-2.63) were similar between the IORT and non-IORT groups. CONCLUSION: IORT significantly improved locoregional control and overall survival in patients with resectable PC, without increasing postoperative complications and operation-related mortality rates.

Construction of Nomograms for Predicting Lung and Bone Metastases in Patients with Intrahepatic Cholangiocarcinoma and Identification of Patients Who Can Benefit from Chemotherapy.

OBJECTIVE: The purpose of our study is to build nomograms for predicting the possibility of lung metastasis (LM) and bone metastasis (BM) in patients with intrahepatic cholangiocarcinoma (ICC). METHODS: 1527 patients diagnosed with ICC between 2010 and 2016 were collected from the Surveillance, Epidemiology, and End Results (SEER) database. Univariable and multivariable logistic regression analyses were used to recognize the predictors of LM and BM, respectively. Then two nomograms were established. We applied the C-index, calibration plot, receiver-operating characteristic (ROC) curve, and decision curve analysis (DCA) to evaluate the novel nomograms. The maximum values of the Youden indexes from the ROC curves were utilized to select the cutoff points of the nomograms. The Kaplan-Meier survival curves were used to evaluate the effect of chemotherapy in different groups. The bootstrap resampling method was chosen for internal validation. RESULTS: Five predictors for LM and three predictors for BM were identified, and two nomograms were constructed. The nomograms had high values of C-indexes, reaching 0.821 (95% CI 0.772-0.871) for LM and 0.759 (95% CI 0.700-0.818) for BM. C-indexes of 0.814 for LM and 0.749 for BM were also observed in internal validation. The calibration plots, ROC curves, and DCAs exhibited favorable performances for predicting LM and BM. The cutoff points of total points in nomograms were 108 for LM and 144 for BM, which could distinguish between high-risk and low-risk groups for LM and BM. Chemotherapy is suggested to undergo for patients in high-risk groups. CONCLUSIONS: The nomograms could assess the possibility of LM and BM in ICC patients and determine the optimal treatment.

Development of a Nomogram to Predict Disease-Specific Survival for Patients After Resection of a Non-Metastatic Adenocarcinoma of the Pancreatic Body and Tail.

BACKGROUND: Models for predicting patient survival after resection of a non-metastatic adenocarcinoma of the pancreatic body and tail (APBT) are scarce. We wished to establish and validate a nomogram to predict disease-specific survival (DSS) of these patients. METHODS: A total of 1,435 patients screened from the Surveillance, Epidemiology, and End Results (SEER) database were included and divided randomly into a training set (TS; n = 1,007) and internal validation set (IVS; n = 428) at a ratio of 7:3. Cox regression analyses were conducted to select independent predictors in the TS, and a nomogram was constructed. The model was subjected to the IVS and an external validation set (EVS) comprising 151 patients from two tertiary hospitals. RESULTS: Five independent risk factors (age at the diagnosis, chemotherapy, tumor grade, T stage, and the lymph node radio) were identified and integrated into the nomogram. Calibration curves indicated that the nomogram could predict DSS at 1, 2, and 3 years accurately. The nomogram had a higher concordance index for predicting DSS compared with that using the 8th edition of the American Joint 23 Committee on Cancer (AJCC8) stage (TS: 0.681 vs. 0.606; IVS: 0.662 vs. 0.590; and EVS: 0.675 vs. 0.608). The nomogram had better discrimination ability and clinical utility than the AJCC8 stage for predicting 1-, 2-, and 3-year DSS. CONCLUSION: Our developed nomogram could accurately predict DSS in patients after resection of a non-metastatic APBT.

Genome-Wide Profiling of Prognostic Alternative Splicing Pattern in Pancreatic Cancer.

Alternative splicing (AS) has a critical role in tumor progression and prognosis. Our study aimed to investigate pancreatic cancer-specific AS events using RNA-seq data, gaining systematic insights into potential prognostic predictors. We downloaded 10,623 genes with 45,313 pancreatic cancer-specific AS events from the Cancer Genome Atlas (TCGA) and SpliceSeq database. Cox univariate analyses of overall survival suggested there was a remarkable association between 6,711 AS events and overall survival in pancreatic cancer patients (P < 0.05). The area under the curves (AUC) of the receiver operator characteristic curves (ROC) of risk score was 0.89 for final prognostic predictor. Results indicated that AS events of DAZAP1, RBM4, ESRP1, QKI, and SF1 were significantly associated with overall survival. The results of FunRich showed that transcription factors KLF7, GABPA, and SP1 were the most highly related to survival-associated AS genes. Furthermore, using DriverDBv2, we identified 13 driver genes associated with survival-associated AS events, including TP53 and CDC27. Thus, we concluded that the aberrant AS patterns in pancreatic cancer patients might serve as prognostic predictors.