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ObjectiveAccumulated evidence has suggested a relatively high recurrence rate in early-stage cervical cancer (CC) patients with risk factors. This study aimed to assess the efficacy and safety of consolidation chemotherapy following adjuvant therapy (concurrent chemoradiotherapy (CCRT) or radiotherapy (RT) alone) in stage IB-IIA CC patients with risk factors.MethodsA total of 237 stage IB-IIA CC patients who received radical surgery between January 2014 and December 2021 were included in the retrospective study. According to the types of adjuvant therapies, the patients were classified into the control group (CCRT or RT alone) and the study group (consolidation chemotherapy following CCRT or RT alone). The propensity score matching (PSM) was used to balance baseline characteristics between the two groups. The primary end points of the study were disease-free survival (DFS) and overall survival (OS).ResultsFor the entire cohort, no significant difference was observed in the DFS or OS between the study and control group, which was also confirmed in the PSM cohort (n=124). The multivariate analysis identified the high-risk factor type was an independent adverse prognostic factor for the patients. In patients with high risk factors, consolidation chemotherapy following adjuvant therapy was significantly associated with better clinical outcomes and identified as an independent prognostic favorable factor. Moreover, this association remained statistically significant in high-risk patients with ≥2 metastatic lymph nodes. In patients with intermediate risk factors, consolidation chemotherapy following adjuvant therapy was unrelated to DFS or OS. The safe assessment demonstrated consolidation chemotherapy following adjuvant therapy was significantly correlated with higher rates of ≥ grade 3 hematologic toxicities in both the global and subgroup analysis stratified by risk factor type.ConclusionConsolidation chemotherapy after adjuvant therapy provided survival benefits in stage IB-IIA CC patients with high risk factors, particularly those with ≥2 metastatic lymph nodes. However, related hematologic toxicities should be alerted in patient management. The actual efficacy and safety of consolidation chemotherapy still need to be investigated in more well-designed clinical trials.

ObjectiveIncreasing studies have highlighted the potential utility of non-invasive prognostic biomarkers in advanced lung cancer patients receiving immune checkpoint inhibitor (ICI) based anti-cancer therapies. Here, a novel prognostic predictor named as C-PLAN integrating C-reactive protein (CRP), Performance status (PS), Lactate dehydrogenase (LDH), Albumin (ALB), and derived Neutrophil-to-lymphocyte ratio (dNLR) was identified and validated in a single-center retrospective cohort.MethodsThe clinical data of 192 ICI-treated lung cancer patients was retrospectively analyzed. The pretreatment levels of CRP, PS, LDH, ALB and dNLR were scored respectively and then their scores were added up to form C-PLAN index. The correlation of C-PLAN index with the progression-free survival (PFS) or overall survival (OS) was analyzed by a Kaplan–Meier model. The multivariate analysis was used to identify whether C-PLAN index was an independent prognostic predictor.ResultsA total of 88 and 104 patients were included in the low and high C-PLAN index group respectively. High C-PLAN index was significantly correlated with worse PFS and OS in ICI-treated lung cancer patients (both p

ObjectiveMultiple myeloma (MM) is a highly characteristic tumor that is influenced by numerous factors that determine its prognosis. Studies indicate that the presence of circulating plasma cells (cPCs) is a detrimental factor that significantly impacts the prognosis of patients with MM.MethodsThis study retrospectively analyzed the prognostic value of cPCs quantified by 10-color flow cytometry in 145 newly diagnosed MM (NDMM) cases in the First Affiliated Hospital of Soochow University from November 2018 to February 2021. The study was approved by the Ethics Committee of the hospital (2021 No. 93).ResultsOf the 145 patients, 99 (68.2%) were detected cPCs. Through receiver operating characteristics (ROC) analysis, an optimal threshold of 0.165% was identified as a predictor for overall survival (OS). The median progression-free survival (PFS) was 33 months in patients with cPCs ≥0.165%, whereas those with cPCs

Background2’,5’-oligoadenylate synthetase 1 (OAS1), has been reported as a tumor driver gene in breast carcinoma and pancreatic carcinoma. However, the role of OAS1 in most tumors has not been reported.MethodsThe original data of 35 tumor types were down load from the TCGA (The Cancer Genome Atlas) database and Human Protein Atlas (HPA) database. TIMER2, Kmplot, UALCAN, and TISIDB tools were used to investigate the expression and function of OAS1, and the role of OAS1 in prognosis, diagnostic value, and immune characteristics of pan-cancer. LUAD and PRAD cell lines, A549, H1975, PC-3 and C4-2 were utilized to perform cell function tests.ResultsOAS1 expression was up-regulated in 12 tumor types and down-regulated in 2 tumor types. High OAS1 expression was correlated with poor prognosis in 6 tumor types, while high OAS1 expression was correlated with good prognosis in 2 tumor types. OAS1 was correlated with molecular subtypes in 8 tumor types and immune subtypes in 12 tumor types. OAS1 was positively associated with the expression of numerous immune checkpoint genes and tumor mutational burden (TMB). OAS1 had potential diagnostic value in 15 tumor types. Silence of OAS1 significantly inhibited the cell proliferation ability, and promoted G2/M cell cycle arrest of LUAD and PRAD cells. Meanwhile, silence of OAS1 enhanced cisplatin-induced apoptosis of LUAD and PRAD cells, but weakened cell migration.ConclusionThis pan-cancer study suggests that OAS1can be used as a molecular biomarker for prognosis in pan-cancer and may play an important role in tumor immune response.

BackgroundPrimary central nervous system lymphoma (PCNSL) is an uncommon variant of non-Hodgkin lymphoma (NHL) with high aggressiveness and poor prognosis. Although complete remission (CR) could be achieved with therapy, some patients remain refractory or recurrently with a worse response to salvage treatment and poor prognosis. No consensus on rescue therapy has been established currently. This study is aimed to evaluate the efficacy of radiotherapy or chemotherapy in first-time relapsed or refractory progressed PCNSL (R/R PCNSL) and analysis the prognostic factors, to explore differences between relapsed and refractory PCNSL.MethodsTotally 105 R/R PCNSL patients from Huashan Hospital between 1 January 2016 and 31 December 2020 were enrolled, underwent salvage radiotherapy or chemotherapy and received response assessments after each course. PFS1 was defined as the time from diagnosis to the first time of recurrence or refractory progression. Statistical analysis was performed with SPSS version 26.0.ResultsResponse and survival were analyzed over a 17.5months (median) follow-up. Compared to relapsed PCNSL (n = 42), refractory PCNSL (n = 63) had a shorter median PFS1 related to deep lesions. 82.4% of cases were discovered as the second relapse or progression. ORR and PFS were both higher in relapsed PCNSL than those in refractory PCNSL. ORR of radiotherapy in both relapsed and refractory PCNSL was higher than that of chemotherapy. Elevated CSF protein and ocular involvement were related to PFS and OS after recurrence respectively in relapsed PCNSL. Age ≥ 60y was unfavorable to OS-R (OS after recurrence or progression) in refractory PCNSL.ConclusionsOur results indicate that relapsed PCNSL responds well to inducing and salvage therapy and has a better prognosis compared to refractory PCNSL. Radiotherapy is effective for PCNSL after the first relapse or progression. Age, CSF protein level, and ocular involvement could be potential factors to predict prognosis.

Objectives: To evaluate the effects of platinum-based neoadjuvant chemotherapy (NACT) on the STING/IFN pathway and tumor-infiltrating lymphocytes (TILs) in non-small cell lung cancer (NSCLC), as well as clinicopathological factors affecting patient survival. Materials and methods: A total of 68 patients aged 34-77 years with NSCLC who received neoadjuvant chemotherapy and surgical treatment from March 2012 to February 2019 were reviewed, and the clinical pathological data and paired tissue specimens before and after NACT were collected. Immunohistochemistry and immunofluorescence were used to detect the protein levels of STING, PD-L1 and IFN-b, and the infiltration density of CD3+ TILs and CD8+TILs. The correlation between the expression of STING, PD-L1, IFN-b and the infiltration density of CD3+ TILs and CD8+ TILs as well as the clinicopathological characteristics before and after NACT was analyzed. The relationship between the related indexes, clinicopathological features and prognosis was also discussed. Results: NACT increased the expression of STING, IFN-β and PD-L1 in tumor cells, and the infiltration of CD3+ and CD8+ TILs. In addition, ypTNM stage, ypN stage, changes in CD3+ TILs and in PD-L1 were associated with DFS (disease-free survival). CD3+ TILs changes and ypN stage were associated with OS (overall survival). Notably, ypN stage and CD3+ TILs changes were independent prognostic factors for DFS and OS. Conclusion: NACT stimulates STING/IFN-β pathway, promotes infiltration of CD3+ and CD8+ TILs, triggers innate and adaptive immunity, and also upregulates PD-L1, which complemented the rationale for neoadjuvant chemotherapy in combination with immunotherapy. In addition, DFS was longer in patients with ypTNM I, ypN0-1, and elevated CD3+TILs after NACT. Patients with ypN0 and elevated CD3+ TILs after NACT had better OS benefits. [ABSTRACT FROM AUTHOR]

BackgroundAngiogenesis is a major promotor of tumor progression and metastasis in gastric adenocarcinoma (STAD). We aimed to develop a novel lncRNA gene signature by identifying angiogenesis-related genes to better predict prognosis in STAD patients.MethodsThe expression profiles of angiogenesis-related mRNA and lncRNA genes were collected from The Cancer Genome Atlas (TCGA). Then, the “limma” package was used to identify differentially expressed genes (DEGs). The expression profiles of angiogenesis-related genes were clustered by consumusclusterplus. The Pearson correlation coefficient was further used to identify lncRNAs coexpressed with angiogenesis-related clustere genes. We used Lasso Cox regression analysis to construct the angiogenesis-related lncRNAs signature. Furthermore, the diagnostic accuracy of the prognostic risk signature were validated by the TCGA training set, internal test sets and external test set. We used multifactor Cox analysis to determine that the risk score is an independent prognostic factor different from clinical characteristics. Nomogram has been used to quantitatively determine personal risk in a clinical environment. The ssGSEA method or GSE176307 data were used to evaluate the infiltration state of immune cells or predictive ability for the benefit of immunotherapy by angiogenesis-related lncRNAs signature. Finally, the expression and function of these signature genes were explored by RT–PCR and colony formation assays.ResultsAmong angiogenesis-related genes clusters, the stable number of clusters was 2. A total of 289 DEGs were identified and 116 lncRNAs were screened to have a significant coexpression relationship with angiogenic DEGs (P value0.5). A six-gene signature comprising LINC01579, LINC01094, RP11.497E19.1, AC093850.2, RP11.613D13.8, and RP11.384P7.7 was constructed by Lasso Cox regression analysis. The multifactor Cox analysis and Nomogram results showed that our angiogenesis-related lncRNAs signature has good predictive ability for some different clinical factors. For immune, angiogenesis-related lncRNAs signature had the ability to efficiently predict infiltration state of 23 immune cells and immunotherapy. The qPCR analysis showed that the expression levels of the six lncRNA signature genes were all higher in gastric adenocarcinoma tissues than in adjacent tissues. The functional experiment results indicated that downregulation of the expression of these six lncRNA signature genes suppressed the proliferation of ASG and MKN45 cells.ConclusionSix angiogenesis-related genes were identified and integrated into a novel risk signature that can effectively assess prognosis and provide potential therapeutic targets for STAD patients.

BackgroundThe mechanism of cuproptosis has recently been reported in lipoylated proteins of the tricarboxylic acid (TCA) cycle. Besides, the role of copper was previously recognized in cancer progression. We evaluated the prognostic value of cuproptosis-related gene expression in hepatocellular carcinoma (HCC).MethodsRemarkable genes were selected both in differential expression analysis and Kaplan-Meier survival analysis from ninety-six cuproptosis-related genes using The Cancer Genome Atlas (TCGA) database. The relationships between clinical characteristics and gene expression were performed with Wilcoxon signed-rank test, Kruskal-Wallis test, and logistic regression. Clinicopathologic factors correlated with overall survival in HCCs conducting univariate and multivariate Cox regression analysis. Gene Expression Profiling Interactive Analysis 2 (GEPIA2) and Human Protein Atlas (HPA) databases were utilized to verify the results. Furthermore, Gene Set Enrichment Analysis (GSEA) identified the potential key pathways that dominate cuproptosis in HCC.ResultsElevated ATP7A, SLC25A3, SCO2, COA6, TMEM199, ATP6AP1, LIPT1, DLAT, PDHA1, MTF1, ACP1, FDX2, NUBP2, CIAPIN1, ISCA2 and NDOR1 expression, as well as declined AOC1, FDX1, MT-CO1, and ACO1 expression were significantly emerged in HCC tumor tissues and were significantly associated with HCCs poor survival. The expressions of screened cuproptosis-related genes were prominently related to clinical features. GSEA analysis reported many key signaling pathways (such as natural killer cell mediated cytotoxicity, TCA cycle, glutathione metabolism, ATP-binding cassette (ABC) transporters, Notch signaling pathway, ErbB signaling pathway, and metabolism of xenobiotics by cytochrome p450) were differentially enriched in HCCs with varying degrees of cuproptosis-related genes expression.ConclusionsThe twenty cuproptosis-related genes might be utilized as new candidate prognostic biomarkers for HCC.

BackgroundNeuroblastoma is the most common malignant extracranial tumor for children. Molecular mechanisms underpinning the pathogenesis of this disease are yet to be fully clarified. This study aimed to identify a novel oncogene that could be used as a biomarker informing the prognosis of neuroblastoma, and to predict its biological functions, using bioinformatics and molecular biology tools.MethodsThree data sets from the TARGET, GSE62564, and GSE85047 databases were used for analysis. Survivals of patients with high or low expression of bub1 were compared, using the Kaplan-Meier curve and log-rank test. Immune infiltration was evaluated using ESTIMATE and MCP-counter algorithms. Synthetic small interfering RNAs (siRNAs) were employed to silence bub1 expression in neuroblastoma cell lines SH-SY5Y and SK-N-SH, in order to characterize its biological functions. Gene enrichment analyses of bub1 were carried out, using Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses.ResultsExpression of bub1 was found to significantly affect overall survival and event-free survival of patients with neuroblastoma, positively correlate with the expressions of tpx2 and the ASPM gene, and negatively correlate with host immune infiltration. Expression of bub1 was elevated in patients with neuroblastoma. Silencing bub1 expression using siRNAs in SH-SY5Y and SK-N-SH resulted in decreased cell growth (p < 0.05), reduced migration (p < 0.05), and increased apoptosis (p < 0.05). Function analysis of bub1 revealed cancer-promoting effects, probably via regulating several important downstream molecules, including that related to the apoptosis process and epithelial-mesenchymal transition.ConclusionWe identified a potential tumor-promoting gene bub1 for neuroblastoma that could also serve as a prognostic biomarker.

BackgroundAlthough most acute promyelocytic leukemia(APL) with low-intermediate risk could survive the induction treatment, early death still a big problem to have effects on overall survival in real world.This study aimed to analyze the clinical characteristics and possible predictors of early death in newly diagnosed patients with low-intermediate-risk acute promyelocytic leukemia.MethodsSixty patients with newly diagnosed low/intermediate-risk APL admitted to Mianyang Central Hospital from January 2013 to December 2021 were retrospectively analyzed.ResultsSixty patients with a median age of 46 years (range, 17-75 years) were included. Fourteen patients (23.3%) were in low-risk group, and 46 patients (76.7%) were in intermediate-risk group. Fourteen patients (23.3%) died during induction treatment. Five patients died of hemorrhage, 5 of severe infection and 4 of differentiation syndrome. Multivariate analysis showed that HGB

BackgroundLung adenocarcinoma (LUAD) is one of the most fatal cancers in the world. Previous studies have shown the increase in glycosylation level, and abnormal expressions of related enzymes are closely related to various cancers. Long non-coding RNAs (lncRNAs) play an important role in the proliferation, metabolism, and migration of cancer cells, but the underlying role of glycosyltransferase (GT)-related lncRNAs in LUAD remains to be elucidated.MethodsWe abstracted 14,056 lncRNAs from The Cancer Genome Atlas (TCGA) dataset and 257 GT-related genes from the Gene Set Enrichment Analysis (GSEA) database. Univariate, LASSO-penalized, and multivariate Cox regression analyses were conducted to construct a GT-related lncRNA prognosis model.ResultsA total of 2,726 GT-related lncRNAs were identified through Pearson’s correlation analysis, and eight of them were utilized to construct a GT-related lncRNA model. The overall survival (OS) of the low-risk group continued to be superior to that of the high-risk group according to the subgroups classified by clinical features. The risk model was proved to have independent prognostic characteristics for LUAD by univariate and multivariate Cox regression analyses. The status of the tumor immune microenvironment and the relevant immunotherapy response was significantly different between the two risk groups. The candidate drugs aimed at LUAD subtype differentiation were identified.ConclusionWe constructed a risk model comprising eight GT-related lncRNAs which was identified as an independent predictor of prognoses to predict patient survival and guide-related treatments for patients with LUAD.

BackgroundIncreasing evidence has suggested that inflammation is related to tumorigenesis and tumor progression. However, the roles of immune-related genes in the occurrence, development, and prognosis of glioblastoma multiforme (GBM) remain to be studied.MethodsThe GBM-related RNA sequencing (RNA-seq), survival, and clinical data were acquired from The Cancer Genome Atlas (TCGA), Genotype-Tissue Expression (GTEx), Chinese Glioma Genome Atlas (CGGA), and Gene Expression Omnibus (GEO) databases. Immune-related genes were obtained from the Molecular Signatures Database (MSigDB). Differently expressed immune-related genes (DE-IRGs) between GBM and normal samples were identified. Prognostic genes associated with GBM were selected by Kaplan–Meier survival analysis, Least Absolute Shrinkage and Selection Operator (LASSO)-penalized Cox regression analysis, and multivariate Cox analysis. An immune-related gene signature was developed and validated in TCGA and CGGA databases separately. The Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses were performed to explore biological functions of the signature. The correlation between immune cell infiltration and the signature was analyzed by single-sample gene set enrichment analysis (ssGSEA), and the diagnostic value was investigated. The gene set enrichment analysis (GSEA) was performed to explore the potential function of the signature genes in GBM, and the protein–protein interaction (PPI) network was constructed.ResultsThree DE-IRGs [Pentraxin 3 (PTX3), TNFSF9, and bone morphogenetic protein 2 (BMP2)] were used to construct an immune-related gene signature. Receiver operating characteristic (ROC) curves and Cox analyses confirmed that the 3-gene-based prognostic signature was a good independent prognostic factor for GBM patients. We found that the signature was mainly involved in immune-related biological processes and pathways, and multiple immune cells were disordered between the high- and low-risk groups. GSEA suggested that PTX3 and TNFSF9 were mainly correlated with interleukin (IL)-17 signaling pathway, nuclear factor kappa B (NF-κB) signaling pathway, tumor necrosis factor (TNF) signaling pathway, and Toll-like receptor signaling pathway, and the PPI network indicated that they could interact directly or indirectly with inflammatory pathway proteins. Quantitative real-time PCR (qRT-PCR) indicated that the three genes were significantly different between target tissues.ConclusionThe signature with three immune-related genes might be an independent prognostic factor for GBM patients and could be associated with the immune cell infiltration of GBM patients.

BackgroundExtramedullary plasmacytoma (EMP) is an extremely rare kind of soft tissue plasma cell neoplasm without bone marrow involvement or other systemic characteristics of multiple myeloma. Primary pulmonary plasmacytoma (PPP), with no specific clinical manifestations, is an exceedingly rare type of EMP. Because of its complexity, PPP is often difficult to diagnose. Computed tomography-guided percutaneous core needle biopsy (CT-guided PCNB) has been shown to have high sensitivity, specificity and accuracy for characterization of pulmonary lesion, particularly if malignancy is suspected. Here we presented a rare case of PPP diagnosed with CT-guided PCNB.Case presentationA 78-year-old female smoker who visited our outpatient clinic for a mass in the left lower lobe of the lung. Pathological based on CT-guided PCNB yielded a PPP with no lymph node or other distant metastasis.ConclusionsExtramedullary plasmacytoma should be considered in the differential diagnosis of a pulmonary mass.

PurposeMacrophage polarization plays an essential role in the tumor microenvironment of brain tumors. However, the role of tumor-associated macrophages (TAMs) in medulloblastoma still remains controversial. Thus, we investigated the distribution of macrophages in medulloblastoma tissues and analyzed the association of TAM recruitment and medulloblastoma patients’ outcomes.MethodsWe obtained a total of 71 paraffin sections from patients with medulloblastoma, and detected the activated phenotype (M1/M2) by monoclonal antibodies for CD68, HLA-DR and CD163 with multiple fluorescence immunohistochemistry method. The number of polarized macrophages was quantified using the InForm software. Outcomes were analyzed according to clinical data and quantified macrophage data.ResultsThe study revealed that TAMs were significantly higher in sonic hedgehog (SHH) medulloblastoma than in other subgroups, and M1 macrophages in metastatic group were significantly higher than those in non-metastatic group. A Kaplan-Meier survival analysis and multivariate Cox regression model showed the correlation of high percentage of total macrophages (P = 0.038, HR = 0.241) and M1 macrophages (P = 0.034, HR = 0.333) with good 5-year progression-free survival (PFS); however, M2 macrophages had no correlation with survival of medulloblastoma patients (P> 0.05).ConclusionHigh percentage of total macrophages and M1 macrophages are correlated with good outcome of medulloblastoma patients. TAMs might be a target of therapy.

ObjectivesAcute myeloid leukemia (AML) is a highly heterogeneous hematologic malignancy with widely variable prognosis. For this reason, a more tailored-stratified approach for prognosis is urgently needed to improve the treatment success rates of AML patients.MethodsIn the investigation of metabolic pattern in AML patients, we developed a metabolism-related prognostic model, which was consisted of metabolism-related gene pairs (MRGPs) identified by pairwise comparison. Furthermore, we analyzed the predictive ability and clinical significance of the prognostic model.ResultsGiven the significant differences in metabolic pathways between AML patients and healthy donors, we proposed a metabolism-related prognostic signature index (MRPSI) consisting of three MRGPs, which were remarkedly related with the overall survival of AML patients in the training set. The association of MRPSI with prognosis was also validated in two other independent cohorts, suggesting that high MRPSI score can identify patients with poor prognosis. The MRPSI and age were confirmed to be independent prognostic factors via multivariate Cox regression analysis. Furthermore, we combined MRPSI with age and constructed a composite metabolism-clinical prognostic model index (MCPMI), which demonstrated better prognostic accuracy in all cohorts. Stratification analysis and multivariate Cox regression analysis revealed that the MCPMI was an independent prognostic factor. By estimating the sensitivity of anti-cancer drugs in different AML patients, we selected five drugs that were more sensitive to patients in MCPMI-high group than those in MCPMI-low group.ConclusionOur study provided an individualized metabolism-related prognostic model that identified high-risk patients and revealed new potential therapeutic drugs for AML patients with poor prognosis.

Acute myeloid leukemia (AML) is usually associated with poor prognosis and low complete remission (CR) rate due to individual biological heterogeneity. Pyroptosis is a special form of inflammatory programmed cell death related to the progression, treatment response, and prognosis of multiple tumors. However, the potential connection of pyroptosis-related genes (PRGs) and AML still remains unclear. We described the genetic and transcriptional alterations of PRGs in 151 AML samples and presented a consensus clustering of these patients into two subtypes with distinct immunological and prognostic characteristics. Cluster A, associated with better prognosis, was characterized by relatively lower PRG expression, activated immune cells, higher immune scores in the tumor microenvironment (TME), and downregulation of immunotherapy checkpoints. Subsequently, a PRG score was constructed to predict overall survival (OS) of AML patients by using univariate and multivariate Cox regression analysis, and its immunological characteristics and predictive capability were further validated by 1,054 AML samples in external datasets. Besides an immune-activated status, low-PRG score cohorts exhibited higher chemotherapeutic drug sensitivity and significant positive correlation with the cancer stem cell (CSC) index. Combined with age, clinical French-American-British (FAB) subtypes, and PRG score, we successfully constructed a nomogram to effectively predict the 1-/3-/5-year survival rate of AML patients, and the predictive capability was further validated in multiple external datasets with a high area under the curve (AUC) value. The various transcriptomic analysis helps us screen significant pyroptosis-related signatures of AML and provide a new clinical application of PRG scores in predicting the prognosis and benefits of treatment for AML patients.

Diffuse large B-cell lymphoma (DLBCL) is a highly heterogeneous non-Hodgkin lymphoma, and the prognosis of DLBCL patients is widely affected by multivariables. Clinical-factors-based prognostic systems stratify the prognosis of DLBCL with certain limitations, and the value of ferritin on the prognosis of DLBCL is unclear. In this study, 225 cases were retrieved from 4 centers of Huaihai Lymphoma Working Group (HHLWG) as the derivation cohort, and 66 cases were from the other 6 centers of HHLWG as external validation cohort. X-Tile program divided ferritin into three groups when applying 175.00 and 391.90 μg/L as the optimal cutoff points. Based on multivariable analysis, ferritin appeared to be a stronger predictor. A total of three variables (ferritin, age, and lactate dehydrogenase) were included for the development of the nomogram. The C-indexes were 0.73 and 0.70 in the derivation and validation cohort, and the calibration curve showed the consistency between the nomogram prediction and the actual observation. In conclusion, Ferritin-based nomogram enhanced the prognostic value of IPI in DLBCL.

BackgroundCD5-positive diffuse large B-cell lymphoma (CD5+ DLBCL) is a rare subtype of DLBCL with invasive clinical features and poor prognosis. Current clinical variables based on prognostic systems for DLBCL are inadequate to accurately stratify the prognosis of CD5+ DLBCL.MethodsA total of 195 CD5+ DLBCL patients were retrospectively recruited from nine centers in Huaihai Lymphoma Working Group. MaxStat analysis was used to identify optimal cutoff points for continuous variables; univariable and multivariable Cox analyses were used for variable selection; Kaplan–Meier curve was used to analyze the value of variables on prognosis; and C-index, Brier score, and decision curve analysis were measured for predicting model performance.ResultsThe derivation and validation cohorts consisted of 131 and 64 patients. Of the whole cohort, median age at diagnosis was 61 years, of whom 100 (51.28%) were males and the 5‐year overall survival rate was 42.1%. MYC, BCL-2, and the coexpression of MYC/BCL-2 could distinguish the survival of CD5+ DLBCL. Multivariable analysis showed that age, IPI, red blood cell count, neutrophil count, MYC expression, and hepatosplenomegaly were independent predictors, and the prognostic nomogram was developed. The C‐index of the nomogram was 0.809 in the derivation and 0.770 in the validation cohort. Decision curve analysis proved that compared with IPI, the specific nomogram showed a better identification in CD5+ DLBCL.ConclusionThe proposed nomogram provided a valuable tool for prognosis prediction in patients with CD5+ DLBCL.

BackgroundTo better define the clinicopathologic characteristics of signet ring cell (SRC) gastric cancer and build a prognostic model for it.MethodsSRC patient information from 2010 to 2015 were identified using Surveillance, Epidemiology, and End Results (SEER) database. Kaplan-Meier method and log-rank test were used to estimate Overall survival (OS) and to determine associations with histologic subtypes. In COX proportional hazards regression model–based univariate and multivariate analyses, significant variables for construction of a nomogram were screened out. The nomogram was validated by means of the concordance index (CI), calibration plots, and receiver operating characteristics (ROCs) curves.ResultsA total of 11,363 gastric cancer patients were enrolled. On dividing the patients into SRC, well-to-moderately differentiated (WMD) adenocarcinoma, and poorly differentiated (PD) adenocarcinoma, differences among these subgroups emerged. SRC patients were more likely to occur in female and young patients than other histologic subtypes. Larger tumors, stage T4, and node stage N3 were more likely to be found in the SRC group. The survival for SRC patients was better than non-SRC patients in stage I. Univariate and multivariate analyses identified age, tumor site, larger tumor size, advanced T classification, advanced N classification, advanced TNM stage, and surgery of primary site as independent prognostic indicators. Then an OS nomogram was formulated.ConclusionsSRC had distinct clinicopathological characteristics. The nomogram provided an accurate tool to evaluate the prognosis of SRC.

Objective: To assess the prognostic value of a model based on pre-treatment T2WI-based radiomic features and postoperative pathological staging in patients with locally advanced rectal cancer who have undergone neoadjuvant chemoradiotherapy. Methods: Radiomic features were derived from T2WI, and a radiomic signature (RS) was established and validated for the prediction of distant metastases (DM). Subsequently, we designed and validated a nomogram model that combined the radiomic signature and postoperative pathological staging for enhanced DM prediction. Performance measures such as the concordance index (C-index) and area under the curve (AUC) were computed to assess the predictive accuracy of the models. Results: A total of 260 patients participated in this study, of whom 197 (75.8%) were male, and the mean age was 57.2 years with a standard deviation of 11.2 years. 15 radiomic features were selected to define the radiomic signature. Patients with a high-risk radiomic signature demonstrated significantly shorter distant metastasis-free survival (DMFS) in both the development and validation cohorts. A nomogram, incorporating the radiomic signature, pathological T stage, and N stage, achieved an area under the curve (AUC) value of 0.72 (95% CI, 0.60-0.83) in the development cohort and 0.83 (95% CI, 0.73-0.92) in the validation cohort. Conclusion: A radiomic signature derived from T2WI-based radiomic features can effectively distinguish patients with varying risks of DM. Furthermore, a nomogram integrating the radiomic signature and postoperative pathological stage proves to be a robust predictor of DMFS. [ABSTRACT FROM AUTHOR]

The aim of this study was to analyze the influence of non-predominant micropapillary pattern in small sized invasive lung adenocarcinoma. A total of 986 lung adenocarcinoma patients with tumor size ≤3 cm were identified and classified according to the IALSC/ATS/ERS classification. Emphasis was placed on the impact of non-predominant micropapillary pattern on disease-free survival (DFS) and overall survival (OS). The relationship between lung adenocarcinoma subtype and lymph node involvement, EGFR mutation and KRAS mutation was also evaluated. A nomogram was developed to predict the probability of 3- and 5-year OS for these patients. The concordance index and calibration plot were used to validate this model. Among all 986 patients, the percentages of lymph node involvement were: 58.1, 50.0, 33.5, 21.4, 21.1, 10.9, 0, and 0% for micropapillary predominant, solid predominant, acinar predominant, papillary predominant, invasive mucinous adenocarcinoma (IMA), lepidic predominant, minimally invasive adenocarcinoma (MIA), adenocarcinoma in situ (AIS), respectively. The frequency of EGFR mutation in the cases of lepidic predominant, acinar predominant, MIA, micropapillary predominant, papillary predominant, solid predominant, IMA, and AIS were 51.1, 45.2, 44.4, 36.8, 29.3, 26.8, 8.3, and 0%, respectively. A non-predominant micropapillary pattern was observed in 344 (38.4%) invasive adenocarcinoma (IAC), and its presence predicted a poorer DFS (median: 56.0 months vs. 66.0 months, P

Objective: To explore a CT-based radiomics model for preoperative prediction of event-free survival (EFS) in patients with hepatoblastoma and to compare its performance with that of a clinicopathologic model.Patients and Methods: Eighty-eight patients with histologically confirmed hepatoblastoma (mean age: 2.28 ± 2.72 years) were recruited from two institutions between 2002 and 2019 for this retrospective study. They were divided into a training cohort (65 patients from institution A) and a validation cohort (23 patients from institution B). Radiomics features were extracted manually from pretreatment CT images in the portal venous (PV) phase. The least absolute shrinkage and selection operator (LASSO) Cox regression model was applied to construct a “radiomics signature” and radiomics score (Rad-score) for EFS prediction. Then, a nomogram incorporating the Rad-score, updated staging system, and significant variables of clinicopathologic risk (age, alpha-fetoprotein (AFP) level, histology subtype, tumor diameter) as the radiomic model, clinicopathologic model, and combined clinicopathologic-radiomic model were built for EFS estimation in the training cohort, the performance of which was assessed in an external-validation cohort with respect to clinical usefulness, discrimination, and calibration.Results: Nine survival-relevant features were selected for a radiomics signature and Rad-score building. Multivariable analysis revealed that histology subtype (P = 0.01), PV (P = 0.001) invasion, and metastasis (P = 0.047) were independent risk factors of EFS. Patients were divided into low- and high-risk groups based on the Rad-score with a cutoff of 0.08 according to survival outcome. The radiomics signature-incorporated nomogram showed good performance (P < 0.001) for EFS estimation (C-Index: 0.810; 95% CI: 0.738–0.882), which was comparable with that of the clinicopathological model for EFS estimation (C-Index: 0.81 vs. 0.85). The radiomics-based nomogram failed to show incremental prognostic value compared with that using the clinicopathologic model. The combined model (radiomics signature plus clinicopathologic parameters) showed significant improvement in the discriminatory accuracy, along with good calibration and greater net clinical benefit, of EFS (C-Index: 0.88; 95% CI: 0.829–0.933).Conclusion: The radiomics signature can be used as a prognostic indicator for EFS in patients with hepatoblastoma. A combination of the radiomics signature and clinicopathologic risk factors showed better performance in terms of EFS prediction in patients with hepatoblastoma, which enabled precise clinical decision-making.

B and T lymphocyte attenuator (BTLA) is a newly identified immune checkpoint molecular belonging to the CD28 immunoglobulin superfamily. However, the expression and clinical value of BTLA in skin cutaneous melanoma (SKCM) has not been widely characterized. We found that BTLA levels were upregulated in metastatic melanoma compared to normal skin tissues and primary melanoma. Higher BTLA was also correlated with improved prognosis in SKCM based on several datasets. The multivariate Cox regression model revealed that BTLA was an independent survival indicator in metastatic melanoma. Tumor microenvironment analysis indicated BTLA was positively associated with the infiltrating levels of different immune cells and the activity of the anti-cancer immunity cycle. Importantly, BTLA accurately predicted the outcome of melanoma patients treated with MAGE-A3 blocker or first-line anti-PD-1. The present findings disclose that BTLA is a reliable biomarker for prognosis and immunotherapeutic response and might contribute to developing novel SKCM immunological treatment strategies.

Tumor-infiltrating lymphocytes (TILs) in gastric cancer are closely related to clinical prognosis; however, little is known regarding the immune microenvironment in this disease. Thus, RNA-sequencing data from gastric cancer patients were downloaded from the Gene Expression Omnibus (GEO). The proportion of immune cells was determined based on a deconvolution algorithm (CIBERSORT), and gene expression profiles were analyzed in the context of clinical outcomes to construct an immune risk score. Data were analyzed using least absolute shrinkage and selection operator (LASSO) and multivariable Cox regression, to identify prognostic markers of gastric cancer survival. The model included four immune cell types: neutrophils, plasma cells, activated CD4+ memory T cells, and T follicular helper cells. Patients were classified into two subgroups based on risk score, and a significant difference in overall survival (OS) was seen between the subgroups in both the training and testing cohorts, particularly in patients with tumor stages ≥T3. Multivariable analysis revealed that both T-stage and risk score were independent prognostic factors for gastric cancer survival [hazard ratio (HR) 1.505; 95% confidence interval (CI) 1.043–2.173, HR 1.686; 95% CI 1.367–2.080]. Risk scores and clinical factors were then integrated into a nomogram to build a model with both good discriminatory power and accuracy in predicting clinical outcomes. Further analysis using gene set enrichment analysis (GSEA) identified strong associations of immune risk with TGF-β and tumor metastasis-related pathways, which could inform research on the molecular mechanisms of gastric cancer. Collectively, the data presented here suggest that an immune risk model can make an important contribution to predictions prognosis in gastric cancer patients.

The modification level of the transcript N6-methyladenosine (m6A), dynamically regulated by methyltransferases, binding proteins and demethylases, is closely related to the occurrence, and progression of tumors. Here, 13 differentially expressed m6A methylation regulators were confirmed in 374 hepatocellular carcinoma (HCC) patients, among which RBM15, YTHDC1, YTHDF1, and YTHDF2 were significantly variant in different stages and grades. Further consensus clustering analysis identified two HCC subtypes (cluster1/2) in this cohort, finding an active role of the m6A methylation regulators in the malignant progression of HCC. Furthermore, GESA enrichment analysis showed that PPAR signaling pathway, and the pathways involved in retinol metabolism and peroxisome were related to tumor progression. Additionally, a 4-gene risk model (ROC = 0.729) that can be used as a prognostic marker and a predictor for clinicopathological characteristics of HCC was constructed via univariate and multivariate Cox regression analyses. Analysis on overall survival and disease-free survival demonstrated that METTL3 and YTHDF1 out of the four genes in the model could serve as independent prognostic factors for HCC. Overall, this study systematically investigated the effect of m6A methylation regulators on the malignant progression of HCC and proposed a 4-gene risk prediction model, laying a theoretical foundation for the further research on HCC prognosis.

Objective: By identifying the clinicopathological characteristics and prognostic influences of patients with triple-positive breast cancer (TPBC) at Xijing Hospital in China compared with those in the United States, this study aims to construct a nomogram model to forecast the overall survival rate (OS) of TPBC patients. Method: The Surveillance, Epidemiology, and End Results (SEER) database was used to screen 5769 patients as the training cohort, and 191 patients from Xijing Hospital were used as the validation cohort. Cox risk-proportional model was applied to select variables and the nomogram model was constructed based on the training cohort. The performance of the model was evaluated by calculating the C-index and generating calibration plots in the training and validation cohorts. Results: Cox multifactorial analysis showed that age, chemotherapy, radiotherapy, M-stage, T-stage, N-stage, and the mode of surgery were all independent risk factors for the prognosis of TPBC patients (all P<0.05). With this premise, the nomogram model was constructed and evaluated. The C-index value of the nomogram model was 0.830 in the training group and 0.914 in the validation group. Moreover, both the calibration and ROC curves for the proposed model exhibited reliable performance, and the clinical decision curve analysis showed that the proposed model can bring clinical benefits. Conclusions: The constructed nomogram can accurately predict individual survival probabilities and may serve as a clinical decision support tool for clinicians to optimize treatment in individuals. [ABSTRACT FROM AUTHOR]

Backgrounds: Lung adenocarcinoma (LUAD) is the most common subtype of lung cancer, which is the leading cause of cancer death. Dysregulation of cell proliferation and death plays a crucial role in the development of LUAD. As of recently, the role of a new form of cell death, cuproptosis, and it has attracted more and more attention. As of yet, it is not clear whether cuproptosis is involved in the progression of LUAD. Methods: An integrated set of bioinformatics tools was utilized to analyze the expression and prognostic significance of cuproptosis-related genes. Meanwhile, a robust risk signature was developed using machine learning based on prognostic cuproptosis-related genes and explored the value of prognostic cuproptosis-related signature for clinical applications, functional enrichment and immune landscape. Lastly, the dysregulation of the cuproptosis-related genes in LUAD was validated by in vitro experiment. Results: In this study, first, cuproptosis-related genes were found to be differentially expressed in LUAD patients of public databases, and nine of them had prognostic value. Next, a cuproptosis-related model with five features (DLTA, MTF1, GLS, PDHB and PDHA1) was constructed to separate the patients into high- and low-risk groups based on median risk score. Internal validation set and external validation set were used for model validation and evaluation. What's more, Enrichment analysis of differential genes and the WGCNA identified that cuproptosis-related signatures affected tumor prognosis by influencing tumor immunity. Small molecule compounds were predicted based on differential expressed genes to improve poor prognosis in the high-risk group and a nomogram was constructed to further advance clinical applications. In closing, our data showed that FDX1 affected the prognosis of lung cancer by altering the expression of cuproptosis-related signature. Conclusion: A new cuproptosis-related signature for survival prediction was constructed and validated by machine learning algorithm and in vitroexperiments to reflect tumor immune infiltration in LUAD patients. The purpose of this article was to provide a potential diagnostic and therapeutic strategy for LUAD. [ABSTRACT FROM AUTHOR]

Introduction: Tyrosine kinase inhibitors (TKIs) that target epidermal growth factor receptor (EGFR) mutations are commonly administered to EGFRpositive lung cancer patients. However, resistance to EGFR-TKIs (mostly gefitinib and erlotinib) is presently a significant problem. Limited studies have focused on an EGFR-TKI resistance-related gene signature (ERS) in lung adenocarcinoma (LUAD). Methods: Gefitinib and erlotinib resistance-related genes were obtained through the differential analyses of three Gene Expression Omnibus datasets. These genes were investigated further in LUAD patients from The Cancer Genome Atlas (TCGA). Patients in the TCGA-LUAD cohort were split into two groups: one for training and one for testing. The training cohort was used to build the ERS, and the testing cohort was used to test it. GO and KEGG analyses were explored for the enriched pathways between the high-risk and low-risk groups. Various software, mainly CIBERSORT and ssGSEA, were used for immune infiltration profiles. Somatic mutation and drug sensitivity analyses were also explored. Results: An ERS based on five genes (FGD3, PCDH7, DEPDC1B, SATB2, and S100P) was constructed and validated using the TCGA-LUAD cohort, resulting in the significant stratification of LUAD patients into high-risk and low-risk groups. Multivariable Cox analyses confirmed that ERS had an independent prognostic value in LUAD. The pathway enrichment analyses showed that most of the genes that were different between the two risk groups were related to the immune system. Further immune infiltration results revealed that a lower immune infiltration score was observed in high-risk patients, and that various leukocytes were significantly related to the ERS. Importantly, samples from the high-risk group showed lower levels of PD-1, PD-L1, and CTLA-4, which are important biomarkers for immunotherapy responses. Patients in the high-risk group also had more gene mutation changes and were more sensitive to chemotherapy drugs like docetaxel and sorafenib. The ERS was also validated in the GSE30219, GSE11969 and GSE72094, and showed a favorable prognostic value for LUAD patients. Discussion: The ERS established during this study was able to predict a poor prognosis for LUAD patients and had great potential for predicting drug responses. [ABSTRACT FROM AUTHOR]

Background: Although most acute promyelocytic leukemia(APL) with lowintermediate risk could survive the induction treatment, early death still a big problem to have effects on overall survival in real world. This study aimed to analyze the clinical characteristics and possible predictors of early death in newly diagnosed patients with low-intermediate-risk acute promyelocytic leukemia. Methods: Sixty patients with newly diagnosed low/intermediate-risk APL admitted to Mianyang Central Hospital from January 2013 to December 2021 were retrospectively analyzed. Results: Sixty patients with a median age of 46 years (range, 17-75 years) were included. Fourteen patients (23.3%) were in low-risk group, and 46 patients (76.7%) were in intermediate-risk group. Fourteen patients (23.3%) died during induction treatment. Five patients died of hemorrhage, 5 of severe infection and 4 of differentiation syndrome. Multivariate analysis showed that HGB <65g/L at diagnosis (OR=38.474, 95%CI: 2.648~558.923, P=0.008) during induction treatment was an independent risk factors for early death in lowintermediate risk APL patients. In survival group, all patients achieved complete remission, the time to achieve remission was 25.87 ± 5.02 days, the average ATO dosage was 0.16 ± 0.03 mg/kg/day. In univariate analysis, there was no statistically significant difference in time span for remission when ATO dosage was in the 0.11~0.16mg/kg/day range. Compared with patients with low-risk APL, those with intermediate-risk APL had higher white blood cell counts (at diagnosis, day 3, day 5 and peak), higher level of lactate dehydrogenase, higher percentage of bone marrow promyelocytes, more platelet transfusions during treatment, and more early deaths (P<0.05). The overall survival of intermediate-risk APL patients seemed worse than those with low-risk APL (c=5.033, P =0.025). Conclusions: In patients with low-intermediate risk APL, HGB <65g/L at diagnosis was an independent risk factors for early death. Remission could still be achieved at low-dose ATO without affecting the required time for lowintermediate risk APL patients. Differences in clinical characteristics were found between low-risk and intermediate-risk APL. The intermediate-risk group had higher early mortality risk than the low-risk group. [ABSTRACT FROM AUTHOR]

Purpose: Cuprotosis is a newly discovered form of non-apoptotic regulated cell death and is characterized by copper-dependent and associated with mitochondrial respiration. However, the prognostic significance and function of cuprotosis-related genes (CRGs) in hepatocellular carcinoma (HCC) are unknown. This study aims to develop cuprotosis-mediated patterns-related gene (CMPRG) prediction models for the prognosis of patients with HCC, exploring the functional underlying the CRGs on the influence of tumor microenvironment (TME) features. Experimental design: This study obtained transcriptome profiling and the corresponding clinical information from the TCGA and GEO databases. Besides, the Cox regression model with LASSO was implemented to build a multi-gene signature, which was then validated in an internal validation set and two external validation sets through Kaplan-Meier, DCA, and ROC analyses. Results: According to the LASSO analysis, we screened out a cuprotosismediated pattern 5-gene combination (including PBK; MMP1; GNAZ; GPC1 and AKR1D1). A nomogram was constructed for the presentation of the final model. The ROC curve assessed the model’s predictive ability, which resulted in an area under the curve (AUC) values ranging from 0.604 to 0.787 underwent internal and two external validation sets. Meanwhile, the risk score divided the patients into two groups of high and low risk, and the survival rate of high-risk patients was significantly lower than that of low-risk patients (P<0.01). The risk score could be an independent prognostic factor in the multifactorial Cox regression analysis (P<0.01). Functional analysis revealed that immune status, mutational loads, and drug sensitivity differed between the two risk groups. Conclusions: In summary, we identified three cuprotosis-mediated patterns in HCC. And CMPRGs are a promising candidate biomarker for HCC early detection, owing to their strong performance in predicting HCC prognosis and therapy. Quantifying cuprotosis-mediated patterns in individual samples may help improve the understanding of multiomic characteristics and guide the development of targeted therapy for HCC. [ABSTRACT FROM AUTHOR]

Background: Lung adenocarcinoma (LUAD) is one of the most fatal cancers in the world. Previous studies have shown the increase in glycosylation level, and abnormal expressions of related enzymes are closely related to various cancers. Long non-coding RNAs (lncRNAs) play an important role in the proliferation, metabolism, and migration of cancer cells, but the underlying role of glycosyltransferase (GT)-related lncRNAs in LUAD remains to be elucidated. Methods: We abstracted 14,056 lncRNAs from The Cancer Genome Atlas (TCGA) dataset and 257 GT-related genes from the Gene Set Enrichment Analysis (GSEA) database. Univariate, LASSO-penalized, and multivariate Cox regression analyses were conducted to construct a GT-related lncRNA prognosis model. Results: A total of 2,726 GT-related lncRNAs were identified through Pearson's correlation analysis, and eight of them were utilized to construct a GT-related lncRNA model. The overall survival (OS) of the low-risk group continued to be superior to that of the high-risk group according to the subgroups classified by clinical features. The risk model was proved to have independent prognostic characteristics for LUAD by univariate and multivariate Cox regression analyses. The status of the tumor immune microenvironment and the relevant immunotherapy response was significantly different between the two risk groups. The candidate drugs aimed at LUAD subtype differentiation were identified. Conclusion: We constructed a risk model comprising eight GT-related lncRNAs which was identified as an independent predictor of prognoses to predict patient survival and guide-related treatments for patients with LUAD. [ABSTRACT FROM AUTHOR]

Background: Increasing evidence has suggested that inflammation is related to tumorigenesis and tumor progression. However, the roles of immune-related genes in the occurrence, development, and prognosis of glioblastoma multiforme (GBM) remain to be studied. Methods: The GBM-related RNA sequencing (RNA-seq), survival, and clinical data were acquired from The Cancer Genome Atlas (TCGA), Genotype-Tissue Expression (GTEx), Chinese Glioma Genome Atlas (CGGA), and Gene Expression Omnibus (GEO) databases. Immune-related genes were obtained from the Molecular Signatures Database (MSigDB). Differently expressed immune-related genes (DE-IRGs) between GBM and normal samples were identified. Prognostic genes associated with GBM were selected by Kaplan-Meier survival analysis, Least Absolute Shrinkage and Selection Operator (LASSO)-penalized Cox regression analysis, and multivariate Cox analysis. An immune-related gene signature was developed and validated in TCGA and CGGA databases separately. The Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses were performed to explore biological functions of the signature. The correlation between immune cell infiltration and the signature was analyzed by single-sample gene set enrichment analysis (ssGSEA), and the diagnostic value was investigated. The gene set enrichment analysis (GSEA) was performed to explore the potential function of the signature genes in GBM, and the protein-protein interaction (PPI) network was constructed. Results: Three DE-IRGs [Pentraxin 3 (PTX3), TNFSF9, and bone morphogenetic protein 2 (BMP2)] were used to construct an immune-related gene signature. Receiver operating characteristic (ROC) curves and Cox analyses confirmed that the 3-gene-based prognostic signature was a good independent prognostic factor for GBM patients. We found that the signature was mainly involved in immune-related biological processes and pathways, and multiple immune cells were disordered between the high- and low-risk groups. GSEA suggested that PTX3 and TNFSF9 were mainly correlated with interleukin (IL)-17 signaling pathway, nuclear factor kappa B (NF-γB) signaling pathway, tumor necrosis factor (TNF) signaling pathway, and Toll-like receptor signaling pathway, and the PPI network indicated that they could interact directly or indirectly with inflammatory pathway proteins. Quantitative real-time PCR (qRT-PCR) indicated that the three genes were significantly different between target tissues. Conclusion: The signature with three immune-related genes might be an independent prognostic factor for GBM patients and could be associated with the immune cell infiltration of GBM patients. [ABSTRACT FROM AUTHOR]

Objective: To analyze clinical behavior of, optimal treatment regimens for, outcomes, and prognosis of 170 patients with neuroendocrine tumors (NETs) of the endometrium. Methods: The Surveillance, Epidemiology, and End Results database was used to identify patients with endometrial NETs diagnosed between 2004 and 2015. Clinical features and treatment regimens were analyzed, and 5-year overall survival (OS) and cancer-specific survival (CSS) were compared among different stages and treatment regimens. Univariate and multivariate analyses were performed to identify independent prognostic factors associated with endometrial NETs. Finally, prognosis was compared between small- and large-cell neuroendocrine carcinoma (SCNEC and LCNEC, respectively) of the endometrium. Results: There were 20, 8, 47, and 95 patients with stage I, II, III, and IV NET, respectively. The 5-year OS rates of patients in each stage were 59.86%, 42.86%, 32.75%, and 6.04%, respectively. The 5-year CSS survival rates were 59.86%, 50.0%, 38.33%, and 6.39%, respectively. In the multivariate analysis, American Joint Committee on Cancer (AJCC) stage and treatment were associated with poor OS, while AJCC stage, nodal metastasis, and treatment were associated with poor CSS. Neither pathological type nor distant metastasis was associated with prognosis. The rate of distant metastasis was significantly higher for LCNEC than for SCNEC, while 5-year OS and CSS rates were significantly lower. Conclusion: Complete surgical treatment should be selected regardless of staging for patients with endometrial NETs. For early-stage disease, individualized postoperative treatment with single chemotherapy or radiotherapy may improve OS and CSS. For advanced-stage disease, comprehensive postoperative adjuvant therapy may improve OS and CSS. [ABSTRACT FROM AUTHOR]

Objectives: Acute myeloid leukemia (AML) is a highly heterogeneous hematologic malignancy with widely variable prognosis. For this reason, a more tailored-stratified approach for prognosis is urgently needed to improve the treatment success rates of AML patients. Methods: In the investigation of metabolic pattern in AML patients, we developed a metabolism-related prognostic model, which was consisted of metabolism-related gene pairs (MRGPs) identified by pairwise comparison. Furthermore, we analyzed the predictive ability and clinical significance of the prognostic model. Results: Given the significant differences in metabolic pathways between AML patients and healthy donors, we proposed a metabolism-related prognostic signature index (MRPSI) consisting of three MRGPs, which were remarkedly related with the overall survival of AML patients in the training set. The association of MRPSI with prognosis was also validated in two other independent cohorts, suggesting that high MRPSI score can identify patients with poor prognosis. The MRPSI and age were confirmed to be independent prognostic factors via multivariate Cox regression analysis. Furthermore, we combined MRPSI with age and constructed a composite metabolism-clinical prognostic model index (MCPMI), which demonstrated better prognostic accuracy in all cohorts. Stratification analysis and multivariate Cox regression analysis revealed that the MCPMI was an independent prognostic factor. By estimating the sensitivity of anti-cancer drugs in different AML patients, we selected five drugs that were more sensitive to patients in MCPMI-high group than those in MCPMI-low group. Conclusion: Our study provided an individualized metabolism-related prognostic model that identified high-risk patients and revealed new potential therapeutic drugs for AML patients with poor prognosis. [ABSTRACT FROM AUTHOR]

Acute myeloid leukemia (AML) is usually associated with poor prognosis and low complete remission (CR) rate due to individual biological heterogeneity. Pyroptosis is a special form of inflammatory programmed cell death related to the progression, treatment response, and prognosis of multiple tumors. However, the potential connection of pyroptosis-related genes (PRGs) and AML still remains unclear. We described the genetic and transcriptional alterations of PRGs in 151 AML samples and presented a consensus clustering of these patients into two subtypes with distinct immunological and prognostic characteristics. Cluster A, associated with better prognosis, was characterized by relatively lower PRG expression, activated immune cells, higher immune scores in the tumor microenvironment (TME), and downregulation of immunotherapy checkpoints. Subsequently, a PRG score was constructed to predict overall survival (OS) of AML patients by using univariate and multivariate Cox regression analysis, and its immunological characteristics and predictive capability were further validated by 1,054 AML samples in external datasets. Besides an immune-activated status, low-PRG score cohorts exhibited higher chemotherapeutic drug sensitivity and significant positive correlation with the cancer stem cell (CSC) index. Combined with age, clinical French-American-British (FAB) subtypes, and PRG score, we successfully constructed a nomogram to effectively predict the 1-/3-/5-year survival rate of AML patients, and the predictive capability was further validated in multiple external datasets with a high area under the curve (AUC) value. The various transcriptomic analysis helps us screen significant pyroptosis-related signatures of AML and provide a new clinical application of PRG scores in predicting the prognosis and benefits of treatment for AML patients. [ABSTRACT FROM AUTHOR]

Diffuse large B-cell lymphoma (DLBCL) is a highly heterogeneous non-Hodgkin lymphoma, and the prognosis of DLBCL patients is widely affected by multivariables. Clinical-factors-based prognostic systems stratify the prognosis of DLBCL with certain limitations, and the value of ferritin on the prognosis of DLBCL is unclear. In this study, 225 cases were retrieved from 4 centers of Huaihai Lymphoma Working Group (HHLWG) as the derivation cohort, and 66 cases were from the other 6 centers of HHLWG as external validation cohort. X-Tile program divided ferritin into three groups when applying 175.00 and 391.90 μg/L as the optimal cutoff points. Based on multivariable analysis, ferritin appeared to be a stronger predictor. A total of three variables (ferritin, age, and lactate dehydrogenase) were included for the development of the nomogram. The C-indexes were 0.73 and 0.70 in the derivation and validation cohort, and the calibration curve showed the consistency between the nomogram prediction and the actual observation. In conclusion, Ferritin-based nomogram enhanced the prognostic value of IPI in DLBCL. [ABSTRACT FROM AUTHOR]

Background: CD5-positive diffuse large B-cell lymphoma (CD5+ DLBCL) is a rare subtype of DLBCL with invasive clinical features and poor prognosis. Current clinical variables based on prognostic systems for DLBCL are inadequate to accurately stratify the prognosis of CD5+ DLBCL. Methods: A total of 195 CD5+ DLBCL patients were retrospectively recruited from nine centers in Huaihai Lymphoma Working Group. MaxStat analysis was used to identify optimal cutoff points for continuous variables; univariable and multivariable Cox analyses were used for variable selection; Kaplan–Meier curve was used to analyze the value of variables on prognosis; and C-index, Brier score, and decision curve analysis were measured for predicting model performance. Results: The derivation and validation cohorts consisted of 131 and 64 patients. Of the whole cohort, median age at diagnosis was 61 years, of whom 100 (51.28%) were males and the 5‐year overall survival rate was 42.1%. MYC, BCL-2, and the coexpression of MYC/BCL-2 could distinguish the survival of CD5+ DLBCL. Multivariable analysis showed that age, IPI, red blood cell count, neutrophil count, MYC expression, and hepatosplenomegaly were independent predictors, and the prognostic nomogram was developed. The C‐index of the nomogram was 0.809 in the derivation and 0.770 in the validation cohort. Decision curve analysis proved that compared with IPI, the specific nomogram showed a better identification in CD5+ DLBCL. Conclusion: The proposed nomogram provided a valuable tool for prognosis prediction in patients with CD5+ DLBCL. [ABSTRACT FROM AUTHOR]

Background: Proficient mismatch repair (pMMR) colorectal adenocarcinoma (CRAC) metastasizes to a greater extent than MMR-deficient CRAC. Prognostic biomarkers are preferred in clinical practice. However, traditional biomarkers screened directly from sequencing are often not robust and thus cannot be confidently utilized. Methods: To circumvent the drawbacks of blind screening, we established a new strategy to identify prognostic biomarkers in the conserved and specific oncogenic pathway and its regulatory RNA network. We performed RNA sequencing (RNA-seq) for messenger RNA (mRNA) and noncoding RNA in six pMMR CRAC patients and constructed a glycosylation-related RNA regulatory network. Biomarkers were selected based on the network and their correlation with the clinicopathologic information and were validated in multiple centers (n = 775). Results: We constructed a competing endogenous RNA (ceRNA) regulatory network using RNA-seq. Genes associated with glycosylation pathways were embedded within this scale-free network. Moreover, we further developed and validated a seven-glycogene prognosis signature, GlycoSig (B3GNT6 , GALNT3 , GALNT8 , ALG8 , STT3B , SRD5A3 , and ALG6) that prognosticate poor-prognostic subtype for pMMR CRAC patients. This biomarker set was validated in multicenter datasets, demonstrating its robustness and wide applicability. We constructed a simple-to-use nomogram that integrated the risk score of GlycoSig and clinicopathological features of pMMR CRAC patients. Conclusions: The seven-glycogene signature served as a novel and robust prognostic biomarker set for pMMR CRAC, highlighting the role of a dysregulated glycosylation network in poor prognosis. [ABSTRACT FROM AUTHOR]

The relationship between m6A-related lncRNAs and prognosis in hepatocellular carcinoma (HCC) is not yet clear. We used Lasso regression to establish a prognostic signature based on m6A-related lncRNAs using a training set from TCGA, and then verified the signature efficacy in a test set. Fluorescence quantitative real-time PCR (qPCR), Survival analysis, clinical risk difference analysis, immune-related analysis, and drug-sensitivity analysis were conducted. The results revealed that 1,651 lncRNAs were differentially expressed in HCC tissues, among which, 163 were m6A-related. Univariate analysis showed that 87 lncRNAs were associated with the overall survival. Six differential m6A-related lncRNAs were validated and selected via Lasso regression to construct a prognostic signature which demonstrated a satisfactory predictive efficacy. In the clinically relevant pathologic stage, histologic grade, and T stage, the risk scores obtained based on this signature showed a statistically significant difference. The high- and low-risk groups exhibited a difference in the tumor immune infiltrating cells, immune checkpoint gene expression, and sensitivity to chemotherapy. In summary, the prognostic signature based on the m6A-related lncRNAs can effectively predict the prognosis of patients and might provide a new vista for the chemotherapy and immunotherapy of HCC. [ABSTRACT FROM AUTHOR]

Background: Few studies have explored the optimal examined lymph node count and lymph node density cutoff values that could be used to predict the survival of patients with penile cancer. We further clarify the prognostic value of lymph node density and examined lymph node count in penile cancer. Methods: The Surveillance, Epidemiology, and End Results (SEER) database was explored to recruit penile cancer patients from 2010 to 2015. A retrospective analysis of penile cancer patients' data from the First Affiliated Hospital of Anhui Medical University was performed for verification (2006–2016). The cutoff values of examined lymph node count and lymph node density were performed according to the ROC curve. Kaplan-Meier survival analysis was used to compare survival differences among different groups. Univariate and multivariate Cox proportional hazard regression analyses were used to determine the significant variables. On the basis of Cox proportional hazards regression model, a nomogram was established and validated by calibration plot diagrams and concordance index (C-index). Results: A total of 528 patients in the Surveillance, Epidemiology, and End Results cohort and 156 patients in the Chinese cohort were included in this study. Using the ROC curve, we found that the recommended cutoff values of ELN and LND were 13 and 9.3%, respectively (P <0.001). Kaplan–Meier curves suggested the significant differences of overall survival among different examined lymph nodes and lymph node density. Multivariate analysis indicated ELN and LND were independent prognostic factor for OS of penile cancer patients. Nomogram showed the contribution of ELN and LND to predicting OS was large. The C-index at 3-, and 5-year were 0.744 for overall survival (95% CI 0.711–0.777). Conclusions: The more lymph nodes examined, the lower the density of lymph nodes, and the higher the long-term survival rate of penile cancer. We recommended 13 examined lymph nodes and lymph node density >9.3% as the cutoff value for evaluating the prognosis of penile cancer patients. [ABSTRACT FROM AUTHOR]

The MDM2 binding protein (MTBP) has been considered an important regulator of human malignancies. In this study, we demonstrate that the high level of MTBP's endogenous expression is correlated with poor prognosis of advanced hepatocellular carcinoma (HCC) patients who received sorafenib. MTBP interacted with the Pregnane X receptor (PXR) and enhanced the transcription factor activity of PXR. Moreover, MTBP enhanced the accumulation of PXR in HCC cells' nuclear and the recruitment of PXR to its downstream gene's (cyp3a4's) promoter region. Mechanically, the knockdown of MTBP in MHCC97-H cells with high levels of MTBP decelerated the clearance or metabolism of sorafenib in HCC cells and led to the resistance of HCC cells to sorafenib. Whereas overexpression of MTBP in in MHCC97-L cells with low levels of MTBP showed the opposite trend. By establishing the interaction between MTBP and PXR, our results indicate that MTBP could function as a co-activator of PXR and could be a promising therapeutic target to enhance the sensitivity of HCC cells to molecular targeting agents. [ABSTRACT FROM AUTHOR]

Background: Micropapillary adenocarcinoma is one of the most aggressive histologic subtypes of lung adenocarcinoma (LADC), and even a minor proportion of micropapillary component (MPC) within the LADC could contribute to poor prognosis. Comprehensive analysis of genetic and immunological features of LADC with different percentages of MPC would help better understand cancer biology of this LADC subtype and direct future treatments. Methods: We performed next-generation sequencing (NGS) for a discovery cohort of 43 LADC patients whose tumors were micro-dissected to separate MPC and non-MPC lesions and a reference cohort of 113 LADC patients. MPC-enriched genetic alterations that were detected in the discovery cohort were then confirmed using a validation cohort of 183 LADC patients. Immunological staining was also conducted on the MPC-containing samples in the discovery cohort. Results: Tumors with a higher percentage of MPC tended to harbor more tumor mutation burdens (TMBs) and chromosome instability (CIN). Some rare genetic events may serve as the genetic landscape to drive micropapillary tumor progression. Specifically, alterations in transcription termination factor 1 (TTF1), brain-specific angiogenesis inhibitor 3 (BAI3), mammalian target of rapamycin (MTOR), and cyclin-dependent kinase inhibitor 2A (CDKN2A) were cross-validated to be enriched in MPC-contained LADC. Additionally, tumors with a higher percentage of MPC were associated with a higher percentage of CD4+, CD8+, and PD-L1+ staining, and some genetic changes that were enriched in MPC, including MET amplification and MTOR mutation, were correlated with increased PD-L1 expression. Conclusion: We identified multiple novel MPC-enriched genetic changes that could help us understand the nature of this aggressive cancer subtype. High MPC tumors tended to have elevated levels of TMBs, T cell infiltration, and immunosuppression than low MPC tumors, implying the potential link between MPC content and sensitivity to immunotherapy. [ABSTRACT FROM AUTHOR]

The aim of this study was to analyze the influence of non-predominant micropapillary pattern in small sized invasive lung adenocarcinoma. A total of 986 lung adenocarcinoma patients with tumor size ≤3 cm were identified and classified according to the IALSC/ATS/ERS classification. Emphasis was placed on the impact of non-predominant micropapillary pattern on disease-free survival (DFS) and overall survival (OS). The relationship between lung adenocarcinoma subtype and lymph node involvement, EGFR mutation and KRAS mutation was also evaluated. A nomogram was developed to predict the probability of 3- and 5-year OS for these patients. The concordance index and calibration plot were used to validate this model. Among all 986 patients, the percentages of lymph node involvement were: 58.1, 50.0, 33.5, 21.4, 21.1, 10.9, 0, and 0% for micropapillary predominant, solid predominant, acinar predominant, papillary predominant, invasive mucinous adenocarcinoma (IMA), lepidic predominant, minimally invasive adenocarcinoma (MIA), adenocarcinoma in situ (AIS), respectively. The frequency of EGFR mutation in the cases of lepidic predominant, acinar predominant, MIA, micropapillary predominant, papillary predominant, solid predominant, IMA, and AIS were 51.1, 45.2, 44.4, 36.8, 29.3, 26.8, 8.3, and 0%, respectively. A non-predominant micropapillary pattern was observed in 344 (38.4%) invasive adenocarcinoma (IAC), and its presence predicted a poorer DFS (median: 56.0 months vs. 66.0 months, P < 0.001) and OS (median: 61.0 months vs. 70.0 months, P < 0.001). After propensity score matching, non-predominant micropapillary pattern retained its unfavorable effect on DFS (P = 0.007) and OS (P = 0.001). Multivariate analysis showed that non-predominant micropapillary pattern was identified as an independent prognostic factor for DFS (P = 0.003) and OS (P < 0.001) in IAC. The nomogram showed good calibration and reliable discrimination ability (C-index = 0.775) to evaluated the 3- and 5-year OS. This retrospective analysis of patients with small sized IAC suggests the value of non-predominant micropapillary pattern to predict poor prognosis. A reliable nomogram model was constructed to provide personalized survival predictions. [ABSTRACT FROM AUTHOR]