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BackgroundIn this study, we evaluated the prognostic value of the plasma levels of Epstein-Barr virus (EBV) DNA in patients with nasopharyngeal carcinoma (NPC) at different treatment stages.MethodsWe retrospectively analyzed the Data of 206 patients with NPC. Pre-neoadjuvant chemotherapy (pre-NACT), post-NACT, post-radiotherapy, and post-treatment plasma EBV DNA levels were used to establish prognostic nomograms. The concordance index (C-index) and calibration curves were used to compare the prognostic accuracy of the nomograms. The results were confirmed in a validation cohort consisting of patients who were tested for EBV DNA levels at all four stages of treatment. The Kaplan-Meier method was used to calculate the progression-free survival (PFS) and overall survival (OS). Survival differences were calculated using the log-rank test.ResultsEBV DNA-positive patients had worse 3-year PFS and 5-year OS than EBV DNA-negative patients; this was true for pre-NACT (PFS: 82.7% vs. 57.3%, P < 0.001; OS: 90.9% vs. 68.7%, P = 0.08) and post-NACT (PFS: 85.0% vs. 50.6%, P < 0.001; OS: 91.7% vs. 65.7%; P = 0.001) EBV DNA levels but not for post-radiotherapy (PFS: 72.2% vs. 60.9%, P = 0.192; OS: 73.1% vs. 77.2%, P = 0.472) or post-treatment (PFS: 77.3% vs. 59.2%, P = 0.063; OS: 77.5% vs. 79.7%, P = 0.644) levels. Nomograms combining pre-NACT and post-NACT EBV DNA levels had a superior prognostic ability than those of post-radiotherapy and post-treatment EBV DNA levels.ConclusionPre-NACT EBV DNA levels combined with post-NACT EBV DNA levels can more reliably predict survival outcomes in patients with NPC.

BackgroundThis study aimed to explore the potential effects of long non-coding RNAs (lncRNAs) in multiple myeloma (MM) patients using two detection methods: high-throughput sequencing and microarray.MethodsIn this study, lncRNAs were detected in 20 newly diagnosed MM patients, with 10 patients analyzed by whole transcriptome-specific RNA sequencing and 10 patients analyzed by microarray (Affymetrix Human Clariom D). The expression levels of lncRNAs, microRNAs, and messenger RNAs (mRNAs) were analyzed, and the differentially expressed lncRNAs identified by both methods were selected. The significant differentially expressed lncRNAs were further validated using PCR.ResultsThis study established the aberrant expression of certain lncRNAs involved in the occurrence of MM, with AC007278.2 and FAM157C showing the most significant differences. The top 5 common pathways identified by the Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis were the chemokine signaling pathway, inflammatory mediator regulation, Th17 cell differentiation, apoptosis, and NF-kappa B signaling pathway. Furthermore, three microRNAs (miRNAs) (miR-4772-3p, miR-617, and miR-618) were found to constitute competing endogenous RNA (ceRNA) networks in both sequencing and microarray analyses.ConclusionsBy the combination analysis, our understanding of lncRNAs in MM will be increased significantly. More overlapping differentially expressed lncRNAs were found to predict therapeutic targets precisely.

Maintenance treatment is a pivotal part in the whole process management of multiple myeloma (MM), which further deepens response and improves survival. However, evidence of maintenance in non-transplant MM patients is inadequate in real-world practice. Here, we retrospectively analyzed the efficacy and survival of 375 non-transplant MM patients from 11 centers between 2010 and 2021 in north China. After a median of seven cycles of front-line regimens, there were 141, 79, and 155 patients receiving lenalidomide maintenance (L-MT), bortezomib maintenance (B-MT), or thalidomide maintenance (T-MT), respectively. Patients on L-MT and B-MT had significantly greater proportions of high-risk cytogenetic abnormalities (HRCAs) detected by fluorescence in situ hybridization (FISH), which was defined as 1q21 gain, 17p deletion, adverse immunoglobulin heavy chain (IgH) translocations. Although the progression-free survival (PFS) and overall survival (OS) were comparable among the three groups, L-MT and B-MT remedied the negative impact of HRCAs on survival (PFS of patients with HRCAs vs. patients without HRCAs: L-MT, 26.9 vs. 39.2 months, p=0.19; B-MT, 20.0 vs. 29.7 months, p=0.36; OS not reached in all groups). Patients with HRCAs in the T-MT group presented inferior clinical outcomes compared to standard-risk patients (PFS, 12.1 vs. 22.8 months, p=0.02, HR=1.8, 95% CI 1.0–3.4; OS, 54.9 months vs. NR, p

ObjectivePrecise risk stratification is increasingly essential in the management of multiple myeloma (MM) as some standard-risk (SR) patients still exhibit similar poor outcomes as genetically high-risk (GHR) patients in the era of novel agents. It has recently been demonstrated that functional high-risk (FHR) patients, those with suboptimal response to first-line induction therapy or early relapse within 12 months, have identifiable molecular characteristics from the SR group in the CoMMpass dataset. However, these findings lack practical validation in the real world.MethodsMM cells purified by CD138 microbeads from newly diagnosed MM (NDMM) patients received fluorescence in situ hybridization and sequencing with a 92-gene Panel. Cytogenetic abnormalities defined GHR patients with t(4;14) or t(14;16) or complete loss of functional P53 or 1q21 gain and International Staging System (ISS) stage 3. SR group was patients who did not fulfill any criteria for GHR or FHR.ResultsThere were 145 patients with NDMM, 78 in the SR group, 56 in the GHR group, and 11 in the FHR group. In the FHR group, eight patients were suboptimal responses to induction therapy, and three relapsed within 12 months. We found that male patients, patients with extra-medullary plasmacytoma (EMD), circulating clonal plasma cells (CPC) ≥0.05%, and P53 mono-allelic inactivation were significantly higher in the FHR group compared to the SR group. After a median follow-up of 21.0 months, the median progression-free survival (PFS) and overall survival (OS) were 5.0 months, 19.1 months and 36.6 months in the FHR, GHR, and SR groups, respectively. Compared to the SR group, FHR patients had a higher frequency of mutations in MKI67, ERN1, and EML4. GO analysis showed that mutations in FHR were enriched for oxidative stress, chromosomal segregation, and hypoxia tolerance.ConclusionThe FHR found in the SR NDMM patient group has unique clinical features, including being male, with EMD and CPC, and genetic characteristics of mutations affecting oxidative stress, chromosome segregation, and hypoxia tolerance. In contrast to previous reports, our data suggested that patients with P53 mono-allelic inactivation should be classified in the GHR group rather than the FHR group.

IntroductionThe diagnostic value of 7 tumor-associated autoantibodies (AABs) including p53, PGP9.5, SOX2, GAGE7, GBU4-5, MEGEA1, and CAGE for the detection of lung cancer has shown inconsistency in several studies. This study aimed to confirm the diagnostic value of 7AABs and to explore whether the diagnostic value would be improved by combining them with 7 traditional tumor-associated antigens (CEA, NSE, CA125, SCC, CA15-3, pro-GRP, and CYFRA21-1) in clinical settings.MethodsThe plasma levels of 7-AABs were detected by enzyme-linked immunosorbent assay (ELISA) in 533 lung cancer cases and 454 controls. The 7 tumor antigens (7-TAs) were measured by Electrochemiluminescence immunoassay with Cobas 6000 (Roche, Basel, Switzerland).ResultsThe positive rate of 7-AABs in the lung cancer group (64.00%) was significantly higher than that of healthy controls (47.90%). The 7-AABs panel was able to discriminate lung cancer from controls with a specificity of 51.50%. After combining the 7-AABs with 7-TAs, the sensitivity showed a significantly enhancement compared with 7AABs panel alone (92.09% vs 63.21%). In patients with resectable lung cancer, the combination of 7-AABs and 7-TAs improved the sensitivity from 63.52% to 97.42%DiscussionIn conclusion, our study found that the diagnostic value of 7-AABs was enhanced when combined with 7-TAs. This combined panel could be used as promising biomarker to detect resectable lung cancer in clinical settings.

ObjectiveTo use machine learning methods to explore overall survival (OS)-related prognostic factors in elderly multiple myeloma (MM) patients.MethodsData were cleaned and imputed using simple imputation methods. Two data resampling methods were implemented to facilitate model building and cross validation. Four algorithms including the cox proportional hazards model (CPH); DeepSurv; DeepHit; and the random survival forest (RSF) were applied to incorporate 30 parameters, such as baseline data, genetic abnormalities and treatment options, to construct a prognostic model for OS prediction in 338 elderly MM patients (>65 years old) from four hospitals in Beijing. The C-index and the integrated Brier score (IBwere used to evaluate model performances.ResultsThe 30 variables incorporated in the models comprised MM baseline data, induction treatment data and maintenance therapy data. The variable importance test showed that the OS predictions were largely affected by the maintenance schema variable. Visualizing the survival curves by maintenance schema, we realized that the immunomodulator group had the best survival rate. C-indexes of 0.769, 0.780, 0.785, 0.798 and IBS score of 0.142, 0.112, 0.108, 0.099 were obtained from the CPH model, DeepSurv, DeepHit, and the RSF model respectively. The RSF model yield best scores from the fivefold cross-validation, and the results showed that different data resampling methods did affect our model results.ConclusionWe established an OS model for elderly MM patients without genomic data based on 30 characteristics and treatment data by machine learning.

Lung cancer is the leading cause of cancer-related deaths worldwide and in China. Screening for lung cancer by low dose computed tomography (LDCT) can reduce mortality but has resulted in a dramatic rise in the incidence of indeterminate pulmonary nodules, which presents a major diagnostic challenge for clinicians regarding their underlying pathology and can lead to overdiagnosis. To address the significant gap in evaluating pulmonary nodules, we conducted a prospective study to develop a prediction model for individuals at intermediate to high risk of developing lung cancer. Univariate and multivariate logistic analyses were applied to the training cohort (n = 560) to develop an early lung cancer prediction model. The results indicated that a model integrating clinical characteristics (age and smoking history), radiological characteristics of pulmonary nodules (nodule diameter, nodule count, upper lobe location, malignant sign at the nodule edge, subsolid status), artificial intelligence analysis of LDCT data, and liquid biopsy achieved the best diagnostic performance in the training cohort (sensitivity 89.53%, specificity 81.31%, area under the curve [AUC] = 0.880). In the independent validation cohort (n = 168), this model had an AUC of 0.895, which was greater than that of the Mayo Clinic Model (AUC = 0.772) and Veterans’ Affairs Model (AUC = 0.740). These results were significantly better for predicting the presence of cancer than radiological features and artificial intelligence risk scores alone. Applying this classifier prospectively may lead to improved early lung cancer diagnosis and early treatment for patients with malignant nodules while sparing patients with benign entities from unnecessary and potentially harmful surgery.Clinical Trial Registration NumberChiCTR1900026233, URL: http://www.chictr.org.cn/showproj.aspx?proj=43370.

BackgroundPancreatic ductal adenocarcinoma (PDAC) is a type of malignant tumor with a five-year survival rate of less than 10%. Gemcitabine (GEM) is the most commonly used drug for PDAC chemotherapy. However, a vast majority of patients with PDAC develop resistance after GEM treatment.MethodsWe screened for GEM resistance genes through bioinformatics analysis. We used immunohistochemistry to analyze 3-oxoacid CoA-transferase 1 (OXCT1) expression in PDAC tissues. The survival data were analyzed using the Kaplan–Meier curve. The expression levels of the genes related to OXCT1 and the NF-κB signaling pathway were quantified using real−time quantitative PCR and western blot analyses. We performed flow cytometry to detect the apoptosis rate. Colony formation assay was performed to measure the cell proliferation levels. The cytotoxicity assays of cells were conducted using RTCA. The downstream pathway of OXCT1 was identified via the Gene Set Enrichment Analysis. Tumor growth response to GEM in vivo was also determined in mouse models.ResultsBioinformatics analysis revealed that OXCT1 is the key gene leading to GEM resistance. Patients with high OXCT1 expression exhibited short relapse-free survival under GEM treatment. OXCT1 overexpression in PDAC cell lines exerted inhibitory effect on apoptosis after GEM treatment. However, the down-regulation of OXCT1 showed the opposite effect. Blocking the NF-κB signaling pathway also reduced GEM resistance of PDAC cells. Tumor growth inhibition induced by GEM in vivo reduced after OXCT1 overexpression. Moreover, the effect of OXCT1 on GEM refractoriness in PDAC cell lines was reversed through using an NF-κB inhibitor.ConclusionOXCT1 promoted GEM resistance in PDAC via the NF-κB signaling pathway both in vivo and in vitro. Our results suggest that OXCT1 could be used as a potential therapeutic target for patients with PDAC.

ObjectiveThis study aims to assess the efficacy and safety of penpulimab (a humanized anti-PD-1 IgG1 antibody) with anlotinib in the first-line treatment of Chinese patients with uHCC.MethodsIn this open-label multicenter phase Ib/II trial, patients with histologically or cytologically confirmed uHCC, without previous systemic treatment, aged 18–75 years old, classified as BCLC stage B (not amenable for locoregional therapy) or C, with Child–Pugh score ≤7 and ECOG performance status ≤1 were enrolled. Patients received penpulimab [200 mg intravenous (i.v.) Q3W] and oral anlotinib (8 mg/day, 2 weeks on/1 week off). The primary endpoint was objective response rate (ORR). Secondary endpoints included safety, disease control rate (DCR), progression-free survival (PFS), time to progression (TTP), duration of response (DoR), and overall survival (OS). This trial is registered with ClinicalTrials.gov (NCT04172571).ResultsAt the data cutoff (December 30, 2020), 31 eligible patients had been enrolled and treated with a median follow-up of 14.7 months (range, 1.4–22.1). The ORR was 31.0% (95% CI, 15.3–50.8%), and the DCR was 82.8% (95% CI, 64.2–94.2%). The median PFS and TTP for 31 patients were 8.8 months (95% CI, 4.0–12.3) and 8.8 months (95% CI, 4.0–12.9) respectively. The median OS was not reached; the 12-month OS rate was 69.0% (95% CI, 48.9–82.5%). Only 19.4% (6/31) of patients had grade 3/4 treatment-related adverse events (TRAEs).ConclusionPenpulimab plus anlotinib showed promising anti-tumor activity and a favorable safety profile as first-line treatment of patients with uHCC.

Identification of novel effective early diagnostic biomarkers may provide alternative strategies to reduce the mortality for non-small cell lung cancer (NSCLC) patients. Circulating long non-coding RNAs (lncRNAs) have emerged as a new class of promising cancer biomarkers. Our study aimed to identify circulating lncRNAs for diagnosing NSCLC. A total 528 plasma samples were continuously collected and allocated to four progressive phases: discovery, training, verification, and expansion phases. The expression of candidate lung cancer related lncRNAs were detected using quantitative reverse-transcriptase polymerase chain reaction (qRT-PCR). We identified a 4-lncRNA panel (RMRP, NEAT1, TUG1, and MALAT1) that provided a high diagnostic value in NSCLC (AUC = 0.86 and 0.89 for training and verification phase, respectively). Subgroup analyses showed that the 4-lncRNA panel had a sensitivity of 78.95% [95% confidence interval (CI) = 62.22%–89.86%] in stage I-II patients and 75.00% (95% CI = 52.95%–89.40%) in patients with small tumor size (≤3cm). Notably, the sensitivity of 4-lncRNA panel was significantly higher than that of routine protein panels in adenocarcinoma (CEA, CA125, and CYFRA21-1, 86.30% vs. 73.96%). Adding 4-lncRNA to protein markers significantly improved the diagnostic capacity in both adenocarcinoma (AUC=0.85, 95% CI = 0.78–0.91) and squamous cell carcinoma (AUC=0.93, 95% CI = 0.86–0.97). In conclusion, we identified a plasma 4-lncRNA panel that has considerable clinical value in diagnosing NSCLC. The 4-lncRNA panel could improve the diagnostic values of routine tumor protein markers in diagnosing NSCLC. Circulating lncRNAs could be used as promising candidates for NSCLC diagnosis.

BackgroundSerum sphingolipids are widely involved in the development of hepatocellular carcinoma (HCC). We investigated the serum sphingolipid profile in patients with HCC or cirrhosis and explored the potential diagnostic efficiency of serum sphingolipid metabolites which may be helpful in differentiating HCC including α-fetoprotein (AFP)-negative HCC from cirrhosis.MethodsSeventy-two HCC patients (including 24 AFP-negative HCC) and 104 cirrhotic patients were consecutively enrolled in this study. High-performance liquid chromatography–tandem mass spectrometry was used to detect a panel of 57 serum sphingolipid metabolites.ResultsTwenty-four sphingolipid metabolites showed significant differences between HCC and cirrhotic patients (all P < 0.05). Sphingosine (d18:1)-1-P was found to have the potential to differentiate HCC from cirrhosis by orthogonal partial least squares discriminant analysis (OPLS-DA). There was no significant difference in the efficacy of Sphingosine (d18:1)-1-P and AFP to distinguish HCC from cirrhosis, and the area under the receiver operating curve (AUC) were 0.85 and 0.83 (P > 0.05), respectively. When the cut-off value of Sphingosine (d18:1)-1-P was set at 56.29 pmol/0.1 ml, the sensitivity and specificity were 79.20% and 78.70%, respectively. Notably, the upregulation of Sphingosine (d18:1)-1-P could also distinguish AFP-negative HCC from cirrhosis with an AUC of 0.79. The sensitivity and specificity were 62.50% and 77.90% at a cut-off value of 56.29 pmol/0.1 ml. Spearman rank correlation analysis revealed that serum Sphingosine (d18:1)-1-P was not correlated with AFP in patients with cirrhosis, AFP-positive HCC, and AFP-negative HCC. Moreover, the difference in the diagnostic efficiency of serum Sphingosine (d18:1)-1-P was not statistically significant between tumor size (≤2 cm vs. >2 cm, P = 0.476). Also, there was no difference among patients with different TNM stages and BCLC stages.ConclusionThe upregulation of serum Sphingosine (d18:1)-1-P exhibits good diagnostic performance for HCC. Particularly, Sphingosine (d18:1)-1-P could also serve as a biomarker for the diagnosis of AFP-negative HCC. These findings may contribute to the non-invasive diagnosis of HCC including AFP-negative HCC.

Increasing evidence indicates that the oncoprotein murine double minute (MDM2) binding protein (MTBP) can be considered a pro-oncogene of human malignancies; however, its function and mechanisms in hepatocellular carcinoma (HCC) are still not clear. In the present work, our results demonstrate that MTBP could function as a co-activator of transcription factor E26 transformation-specific sequence (ETS-1), which plays an important role in HCC cell proliferation and/or metastasis and promotes proliferation of HCC cells. Using luciferase and real-time polymerase chain reaction (qPCR) assays, MTBP was found to enhance the transcription factor activation of ETS-1. The results from chromatin co-immunoprecipitation showed that MTBP enhanced the recruitment of ETS-1 to its downstream gene's (mmp1's) promoter region with ETS-1 binding sites. In cellular and nude mice models, overexpression of MTBP was shown to promote the proliferation of MHCC97-L cells with low endogenous MTBP levels, whereas the knockdown of MTBP led to inhibition of the proliferation of MHCC97-H cells that possessed high endogenous levels of MTBP. The effect of MTBP on ETS-1 was confirmed in the clinical specimens; the expression of MTBP was positively correlated with the downstream genes of ETS-1, mmp3 , mmp9 , and uPA . Therefore, by establishing the role of MTBP as a novel co-activator of ETS-1, this work expands our knowledge of MTBP or ETS-1 and helps to provide new ideas concerning HCC-related research., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2022 Wang, Chu, Zhijie, Bi, Lixin, Zhuang, Xiaofeng, Niu, Zhang, Xi and Li.)

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., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2021 Jiang, Ma, Han, Chu, Ma, Shen, Liu, Li, Hou and Bi.)