Diagnostic Model for Proliferative HCC Using LI-RADS: Assessing Therapeutic Outcomes in Hepatectomy and TKI-ICI Combination.

BACKGROUND: Proliferative hepatocellular carcinoma (HCC), aggressive with poor prognosis, and lacks reliable MRI diagnosis. PURPOSE: To develop a diagnostic model for proliferative HCC using liver imaging reporting and data system (LI-RADS) and assess its prognostic value. STUDY TYPE: Retrospective. POPULATION: 241 HCC patients underwent hepatectomy (90 proliferative HCCs: 151 nonproliferative HCCs), divided into the training (N = 167) and validation (N = 74) sets. 57 HCC patients received combination therapy with tyrosine kinase inhibitors (TKIs) and immune checkpoint inhibitors (ICIs). FIELD STRENGTH/SEQUENCE: 3.0 T, T1- and T2-weighted, diffusion-weighted, in- and out-phase, T1 high resolution isotropic volume excitation and dynamic gadoxetic acid-enhanced imaging. ASSESSMENT: LI-RADS v2018 and other MRI features (intratumoral artery, substantial hypoenhancing component, hepatobiliary phase peritumoral hypointensity, and irregular tumor margin) were assessed. A diagnostic model for proliferative HCC was established, stratifying patients into high- and low-risk groups. Follow-up occurred every 3-6 months, and recurrence-free survival (RFS), progression-free survival (PFS) and overall survival (OS) in different groups were compared. STATISTICAL TESTS: Fisher's test or chi-square test, t-test or Mann-Whitney test, logistic regression, Harrell's concordance index (C-index), Kaplan-Meier curves, and Cox proportional hazards. Significance level: P < 0.05. RESULTS: The diagnostic model, incorporating corona enhancement, rim arterial phase hyperenhancement, infiltrative appearance, intratumoral artery, and substantial hypoenhancing component, achieved a C-index of 0.823 (training set) and 0.804 (validation set). Median follow-up was 32.5 months (interquartile range [IQR], 25.1 months) for postsurgery patients, and 16.8 months (IQR: 13.2 months) for combination-treated patients. 99 patients experienced recurrence, and 30 demonstrated tumor nonresponse. Differences were significant in RFS and OS rates between high-risk and low-risk groups post-surgery (40.3% vs. 65.8%, 62.3% vs. 90.1%, at 5 years). In combination-treated patients, PFS rates differed significantly (80.6% vs. 7.7% at 2 years). DATA CONCLUSION: The MR-based model could pre-treatment identify proliferative HCC and assist in prognosis evaluation. TECHNICAL EFFICACY: Stage 2.

Preoperative Gadoxetic Acid-Enhanced MRI Features for Evaluation of Vessels Encapsulating Tumor Clusters and Microvascular Invasion in Hepatocellular Carcinoma: Creating Nomograms for Risk Assessment.

BACKGROUND: Vessels encapsulating tumor cluster (VETC) and microvascular invasion (MVI) have a synergistic effect on prognosis assessment and treatment selection of hepatocellular carcinoma (HCC). Preoperative noninvasive evaluation of VETC and MVI is important. PURPOSE: To explore the diagnosis value of preoperative gadoxetic acid (GA)-enhanced magnetic resonance imaging (MRI) features for MVI, VETC, and recurrence-free survival (RFS) in HCC. STUDY TYPE: Retrospective. POPULATION: 240 post-surgery patients with 274 pathologically confirmed HCC (allocated to training and validation cohorts with a 7:3 ratio) and available tumor marker data from August 2014 to December 2021. FIELD STRENGTH/SEQUENCE: 3-T, T1-, T2-, diffusion-weighted imaging, in/out-phase imaging, and dynamic contrast-enhanced imaging. ASSESSMENT: Three radiologists subjectively reviewed preoperative MRI, evaluated clinical and conventional imaging features associated with MVI+, VETC+, and MVI+/VETC+ HCC. Regression-based nomograms were developed for HCC in the training cohort. Based on the nomograms, the RFS prognostic stratification system was further. Follow-up occurred every 3-6 months. STATISTICAL TESTS: Chi-squared test or Fisher's exact test, Mann-Whitney U-test or t-test, least absolute shrinkage and selection operator-penalized, multivariable logistic regression analyses, receiver operating characteristic analysis, Harrell's concordance index (C-index), Kaplan-Meier plots. Significance level: P < 0.05. RESULTS: In the training group, 44 patients with MVI+ and 74 patients with VETC+ were histologically confirmed. Three nomograms showed good performance in the training (C-indices: MVI+ vs. VETC+ vs. MVI+/VETC+, 0.892 vs. 0.848 vs. 0.910) and validation (C-indices: MVI+ vs. VETC+ vs. MVI+/VETC+, 0.839 vs. 0.810 vs. 0.855) cohorts. The median follow-up duration for the training cohort was 43.6 (95% CI, 35.0-52.2) months and 25.8 (95% CI, 16.1-35.6) months for the validation cohort. Patients with either pathologically confirmed or nomogram-estimated MVI, VETC, and MVI+/VETC+ suffered higher risk of recurrence. DATA CONCLUSION: GA-enhanced MRI and clinical variables might assist in preoperative estimation of MVI, VETC, and MVI+/VETC+ in HCC. EVIDENCE LEVEL: 4 TECHNICAL EFFICACY: Stage 2.

Long-term evolution of LR-2, LR-3 and LR-4 observations in HBV-related cirrhosis based on LI-RADS v2018 using gadoxetic acid-enhanced MRI.

PURPOSE: To investigate the long-term evolution of LR-2, LR-3 and LR-4 observations in patients with hepatitis B virus (HBV)-related cirrhosis based on LI-RADS v2018 and identify predictors of progression to a malignant category on serial gadoxetic acid-enhanced magnetic resonance imaging (Gd-EOB-MRI). METHODS: This retrospective study included 179 cirrhosis patients with untreated indeterminate observations who underwent Gd-EOB-MRI exams at baseline and during the follow-up period between June 2016 and December 2021. Two radiologists independently assessed the major features, ancillary features, and LI-RADS category of each observation at baseline and follow-up. In cases of disagreement, a third radiologist was consulted for consensus. Cumulative incidences for progression to a malignant category (LR-5 or LR-M) and to LR-4 or higher were analyzed for each index category using Kaplan‒Meier methods and compared using log-rank tests. The risk factors for malignant progression were evaluated using a Cox proportional hazard model. RESULTS: A total of 213 observations, including 74 (34.7%) LR-2, 95 (44.6%) LR-3, and 44 (20.7%) LR-4, were evaluated. The overall cumulative incidence of progression to a malignant category was significantly higher for LR-4 observations than for LR-3 or LR-2 observations (each P < 0.001), and significantly higher for LR-3 observations than for LR-2 observations (P < 0.001); at 3-, 6-, and 12-month follow-ups, the cumulative incidence of progression to a malignant category was 11.4%, 29.5%, and 39.3% for LR-4 observations, 0.0%, 8.5%, and 19.6% for LR-3 observations, and 0.0%, 0.0%, and 0.0% for LR-2 observations, respectively. The cumulative incidence of progression to LR-4 or higher was higher for LR-3 observations than for LR-2 observations (P < 0.001); at 3-, 6-, and 12-month follow-ups, the cumulative incidence of progression to LR-4 or higher was 0.0%, 8.5%, and 24.6% for LR-3 observations, and 0.0%, 0.0%, and 0.0% for LR-2 observations, respectively. In multivariable analysis, nonrim arterial phase hyperenhancement (APHE) [hazard ratio (HR) = 2.13, 95% CI 1.04-4.36; P = 0.038], threshold growth (HR = 6.50, 95% CI 2.88-14.65; P <0.001), and HBP hypointensity (HR = 16.83, 95% CI 3.97-71.34; P <0.001) were significant independent predictors of malignant progression. CONCLUSION: The higher LI-RADS v2018 categories had an increasing risk of progression to a malignant category during long-term evolution. Nonrim APHE, threshold growth, and HBP hypointensity were the imaging features that were significantly predictive of malignant progression.

A multivariate model based on gadoxetic acid-enhanced MRI using Li-RADS v2018 and other imaging features for preoperative prediction of dual­phenotype hepatocellular carcinoma.

OBJECTIVE: To investigate the diagnostic value of liver imaging reporting and data system (LI-RADS) v2018 and other imaging features in dual-phenotype hepatocellular carcinoma (DPHCC), establish a prediagnostic model based on gadoxetic acid-enhanced MRI, and explore the prognostic significance after surgery of the DPHCC. MATERIALS AND METHODS: Preoperative enhanced MRI findings and the clinical and pathological data of patients with surgically confirmed HCC were analysed retrospectively. Image analysis was based on LI-RADS v2018 and other image features. Univariate analysis was used to screen for predictive factors of DPHCC, and multivariate logistic regression analysis was used to determine the predictive factors. A regression diagnostic model was established. Receiver operating characteristic (ROC) curve analysis was used to determine the critical value, area under curve (AUC), and the corresponding 95% confidence interval (95% CI). The diagnostic performance was verified by fivefold cross-validation. Cox regression analysis was used to determine the prognostic factors associated with early recurrence after surgical resection. RESULTS: In total, 158 patients were included, of whom 79 had DPHCC and 79 had non-DPHCC. Multivariate analysis showed that rim arterial phase hyperenhancement (Rim APHE) and targetoid restriction were independent risk factors for DPHCC (P < 0.05). The AUC (95% CI) of the model was 0.862 (0.807-0.918), sensitivity was 81.01%, and specificity was 89.874%. Cox regression analysis showed that DPHCC, microvascular invasion, tumour diameter, and an increase of alpha-fetoprotein were independent factors for recurrence. CONCLUSION: Rim APHE and targetoid restriction were sensitive imaging features of DPHCC before surgery, and the identification of DPHCC has important prognostic significance for early recurrence.

A Machine Learning Model to Predict Survival and Therapeutic Responses in Multiple Myeloma.

Multiple myeloma (MM) is a highly heterogeneous hematologic tumor. Ubiquitin proteasome pathways (UPP) play a vital role in its initiation and development. We used cox regression analysis and least absolute shrinkage and selector operation (LASSO) to select ubiquitin proteasome pathway associated genes (UPPGs) correlated with the overall survival (OS) of MM patients in a Gene Expression Omnibus (GEO) dataset, and we formed this into ubiquitin proteasome pathway risk score (UPPRS). The association between clinical outcomes and responses triggered by proteasome inhibitors (PIs) and UPPRS were evaluated. MMRF CoMMpass was used for validation. We applied machine learning algorithms to MM clinical and UPPRS in the whole cohort to make a prognostic nomogram. Single-cell data and vitro experiments were performed to unravel the mechanism and functions of UPPRS. UPPRS consisting of 9 genes showed a strong ability to predict OS in MM patients. Additionally, UPPRS can be used to sort out the patients who would gain more benefits from PIs. A machine learning model incorporating UPPRS and International Staging System (ISS) improved survival prediction in both datasets compared to the revisions of ISS. At the single-cell level, high-risk UPPRS myeloma cells exhibited increased cell adhesion. Targeted UPPGs effectively inhibited myeloma cells in vitro. The UPP genes risk score is a helpful tool for risk stratification in MM patients, particularly those treated with PIs.

A model incorporating histopathology and preoperative gadoxetic acid-enhanced MRI to predict early recurrence of hepatocellular carcinoma without microvascular invasion after curative hepatectomy.

OBJECTIVES: To assess the predictive value of preoperative gadoxetic acid (GA)-enhanced magnetic resonance imaging (MRI) features and postoperative histopathological grading for early recurrence of hepatocellular carcinoma (HCC) without microvascular invasion (MVI) after curative hepatectomy. METHODS: A total of 85 MVI-negative HCC cases were retrospectively analyzed. Cox analyses were used to identify the independent predictors of early recurrence (within a 24 months span). The clinical prediction Model-1 or Model-2 was established without or with postoperative pathological factor, respectively. Nomogram models were constructed and receiver operating characteristic (ROC) curve analysis was used to assess the models' predictive ability. Internal validation of the prediction models for early HCC recurrence was performed using a bootstrap re-sampling approach. RESULTS: In the multivariate cox regression analysis, Edmondson-Steiner grade, peritumoral hypointensity on hepatobiliary phase (HBP), and relative intensity ratio (RIR) in HBP were identified as independent variables associated with early recurrence. The C-index of the nomogram models and internal validation were both between 0.7 and 0.8, showing good model fitting and calibration effects. The area under the ROC curve (AUC) was 0.781 for Model-1 based on the two preoperative MRI factors. When a third factor, the Edmondson-Steiner grade, was included (Model-2), the AUC increased to 0.834, and the sensitivity increased from 71.4 to 96.4%. CONCLUSIONS: Edmondson-Steiner grade, peritumoral hypointensity on HBP, and RIR on HBP can help predict early recurrence of MVI-negative HCC. In comparison with Model-1 (only imaging features), Model-2 (imaging features + histopathological grades) increases the sensitivity in predicting early recurrence of HCC without MVI. ADVANCES IN KNOWLEDGE: Preoperative GA-enhanced MRI signs are of great value in predicting early postoperative recurrence of HCC without MVI, and a combined pathological model was established to evaluate the feasibility and effectiveness of this technique.

Single-cell atlas of the immune microenvironment reveals macrophage reprogramming and the potential dual macrophage-targeted strategy in multiple myeloma.

The tumour microenvironment (TME) plays a critical role in disease progression in multiple myeloma (MM). This study aimed to present an atlas of MM-TME in disease progression and explore TME-directed therapeutic strategies. We performed single-cell RNA sequencing (scRNAseq) in samples from different disease stages. We validated the findings by bulk RNAseq, flow cytometry (FCM) and in vitro and in vivo functional experiments. We delineated a compromised TME during disease progression, characterized by enrichment of exhausted NK cells and CD8+ T cells and reprogramming of macrophages (MPs). The reprogrammed tumour-associated MPs (TAMs) displayed a mixed phenotype showing both M1 and M2 features, with two TAM clusters exclusively present in the MM stage showing higher M2 scores. We validated the mixed M1/M2 phenotype in TAMs in a clinical cohort and verified phagocytic dysfunction in reprogrammed TAMs. Cellular interaction analysis identified two enriched ligand-receptor pairs between MPs and malignant plasma cells (PCs), including the SIRPA-CD47 pathway suppressing phagocytosis and the CD74-MIF (macrophage inhibitory factor) reshaping the phenotype of MPs. The expression of CD47 and MIF correlated with disease progression and adverse outcomes. We designed a dual-MP-targeted strategy by combining an anti-CD47 antibody and MIF inhibitor to activate phagocytosis and repolarize MP to a functional phenotype and proved its potent antitumour effect in vitro and in vivo. We drafted alterations in MM-TME during disease progression and unravelled TAM's reprogramming. The dual MP-targeted approach blocking both CD47 and MIF showed potent antitumour effects.

Prediction for Aggressiveness and Postoperative Recurrence of Hepatocellular Carcinoma Using Gadoxetic Acid-Enhanced Magnetic Resonance Imaging.

RATIONALE AND OBJECTIVES: To investigate the predictive value of gadoxetic acid-enhanced magnetic resonance imaging (MRI) features on the pathologic grade, microvascular invasion (MVI), and cytokeratin-19 (CK19) expression in hepatocellular carcinomas (HCC), and to evaluate their association with postoperative recurrence of HCC. MATERIALS AND METHODS: This retrospective study included 147 patients with surgically confirmed HCCs who underwent gadoxetic-enhanced MRI. The lesions were evaluated quantitatively in terms of the relative enhancement ratio (RER), and qualitatively based on imaging features and clinical parameters. Logistic regression analyses were performed to investigate the value of these parameters in predicting the pathologic grade, MVI, and CK19 in HCC. Predictive factors for postoperative recurrence were determined using a Cox proportional hazards model. RESULTS: Peritumoral enhancement (odds ratio [OR], 3.396; p = 0.025) was an independent predictor of high pathologic grades. Serum protein induced by vitamin K absence or antagonist (PIVKA) level > 40 mAU/mL (OR, 3.763; p = 0.018) and peritumoral hypointensity (OR, 4.343; p = 0.003) were independent predictors of MVI. Predictors of CK19 included serum alpha-fetoprotein (AFP) level > 400 ng/mL (OR, 4.576; p = 0.005), rim enhancement (OR, 5.493; p = 0.024), and lower RER (OR, 0.013; p = 0.011). Peritumoral hypointensity (hazard ratio [HR], 1.957; p = 0.027) and poor pathologic grades (HR, 2.339; p = 0.043) were independent predictors of recurrence. CONCLUSION: We demonstrated the value of preoperative gadoxetic-enhanced MRI in predicting aggressive pathological features of HCC. Poor pathologic grades and peritumoral hypointensity may independently predict the recurrence of HCC.

Using pre-operative radiomics to predict microvascular invasion of hepatocellular carcinoma based on Gd-EOB-DTPA enhanced MRI.

OBJECTIVES: We aimed to investigate the value of performing gadolinium-ethoxybenzyl-diethylenetriamine pentaacetic acid (Gd-EOB-DTPA) enhanced magnetic resonance imaging (MRI) radiomics for preoperative prediction of microvascular invasion (MVI) of hepatocellular carcinoma (HCC) based on multiple sequences. METHODS: We randomly allocated 165 patients with HCC who underwent partial hepatectomy to training and validation sets. Stepwise regression and the least absolute shrinkage and selection operator algorithm were used to select significant variables. A clinicoradiological model, radiomics model, and combined model were constructed using multivariate logistic regression. The performance of the models was evaluated, and a nomogram risk-prediction model was built based on the combined model. A concordance index and calibration curve were used to evaluate the discrimination and calibration of the nomogram model. RESULTS: The tumour margin, peritumoural hypointensity, and seven radiomics features were selected to build the combined model. The combined model outperformed the radiomics model and the clinicoradiological model and had the highest sensitivity (90.89%) in the validation set. The areas under the receiver operating characteristic curve were 0.826, 0.755, and 0.708 for the combined, radiomics, and clinicoradiological models, respectively. The nomogram model based on the combined model exhibited good discrimination (concordance index = 0.79) and calibration. CONCLUSIONS: The combined model based on radiomics features of Gd-EOB-DTPA enhanced MRI, tumour margin, and peritumoural hypointensity was valuable for predicting HCC microvascular invasion. The nomogram based on the combined model can intuitively show the probabilities of MVI.

Combined Efficacy of CXCL5, STC2, and CHI3L1 in the Diagnosis of Colorectal Cancer.

Objective: To improve the diagnostic capacity of serum biomarkers for colorectal cancer (CRC), we introduced three novel indicators, namely, the C-X-C motif chemokine ligand 5 (CXCL5), stanniocalcin 2 (STC2), and chitinase 3 like 1 (CHI3L1) and assessed their performances in the detection of CRC. Methods: A total of 887 serum samples (153 health, 342 polyps, and 392 CRCs) were collected. Concentrations of CXCL5, STC2, and CHI3L1 were measured by the ELISA. CEA and CA199 were determined by electrochemiluminescence. Binary logistic regression was used to build the combination model. ROC analysis was used to evaluate the performance of biomarkers alone or in combination. Results: Model_2 that based on CXCL5, STC2, and CHI3L1 was the best approach in discriminating CRC from non-CRC controls (AUC, 0.943 (0.922-0.960); sensitivity, 0.848; specificity, 0.917; and accuracy, 0.887 in the training cohort and 0.959 (95% CI 0.927-0.980), 0.878, 0.917, and 0.900 in the testing cohort, respectively). In the detection of early CRC, Model_2 revealed AUC, sensitivity, specificity, and accuracy of 0.925 (0.897-0.947), 0.793, 0.917, and 0.886 in the training cohort and those of 0.926 (0.979-0.959), 0.786, 0.931, and 0.898 in the testing cohort. Furthermore, Model_2 exhibited an excellent diagnostic performance in CEA-negative cases (0.938 (0.913-0.957), 0.826, 0.917, and 0.888 in the training cohort and 0.961 (0.925-0.983), 0.887, 0.931, and 0.918 in the testing cohort). As used alone, STC2 achieved the capacities that is second only to that of Model_2 (0.866 (0.837-0.892), 0.859, 0.842, and 0.853 in the training cohort and 0.887 (0.842-0.923), 0.922, 0.799, and 0.853 in the testing cohort). STC2 alone also yielded acceptable results for early CRC detection (0.815 (0.776-0.849), 0.767, 0.849, and 0.829 in the training cohort and 0.870 (0.812-0.914), 0.952, 0.799, and 0.833 in the testing cohort). Moreover, STC2 maintained diagnostic accuracy for CRC patients with negative CEA (0.874 (0.842-0.901), 0.862, 0.849, and 0.853 in the training cohort and 0.898 (0.848-0.936), 0.930, 0.801, and 0.842 in the testing cohort). In comparison, the performances of the CEA and CA199 based Model_1 were far from satisfactory, especially in early cases (0.767 (0.726-0.805), 0.491, 0.863, and 0.771 in the training cohort and 0.817 (0.754-0.870), 0.476, 0.889, and 0.796 in the testing cohort). Conclusions: STC2 was a promising serum biomarker for CRC diagnosis either used alone or in combination with CXCL5 and CHI3L1.

The role of KIAA1191 in the necroptotic pathway of multiple myeloma.

Multiple myeloma (MM) is an incurable plasma cell malignancy, and International Staging System (ISS) is used to predict the outcomes of MM patients. However, ISS stage is imperfect, and there might exist other factors correlated with prognosis of MM patients. Expression profiles and clinical information of 340 newly diagnosed MM patients from GEO database and 105 newly diagnosed MM patients from our hospital were analyzed, and LASSO regression was used to screen genes associated with both overall survival and progression-free survival of MM patients. Nomogram was constructed to predict outcomes of MM patients. Then, CCK8 and transwell assays were used to evaluate the proliferation and migration ability of MM cells; flow cytometry was performed to verify whether MM cells underwent necroptosis. Quantitative real-time PCR and western blot were performed to evaluate gene expressions. We found that KIAA1191 was associated with both overall survival and progression-free survival of MM patients. Furthermore, KIAA1191 high expression suppressed the proliferation and migration of MM cells; upregulated the expression of RIP1, RIP3, and CYLD, and restored the TNF-α/z-VAD-induced necroptosis. Besides, KIAA1191 overexpression had a synergistic effect with bortezomib on the proliferation capability of MM cells.

Correlation of radiomic features on dynamic contrast-enhanced magnetic resonance with microvessel density in hepatocellular carcinoma based on different models.

OBJECTIVE: To explore the correlations of radiomic features of dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) with microvessel density (MVD) in patients with hepatocellular carcinoma (HCC), based on single-input and dual-input two-compartment extended Tofts (SITET and DITET) models. METHODS: We compared the quantitative parameters of SITET and DITET models for DCE-MRI in 30 patients with HCC using paired sample t-tests. The correlations of SITET and DITET model parameters with CD31-MVD and CD34-MVD were analyzed using Pearson's correlation analysis. A diagnostic model of CD34-MVD was established and the diagnostic abilities of models for MVD were analyzed using receiver operating characteristic curve (ROC) analysis. RESULTS: There were significant differences between the quantitative parameters in the two kinds of models. Compared with SITET, DITET parameters showed better correlations with CD31-MVD and CD34-MVD. The Ktrans and Ve radiomics features of the DITET model showed high efficiency for predicting the level of CD34-MVD according to ROC analysis, with areas under curves of 0.83 and 0.94, respectively. CONCLUSION: Compared with SITET, the DITET model provides a better indication of the microcirculation of HCC and is thus more suitable for examining patients with HCC.

Single-Cell Transcriptomes Combining with Consecutive Genomics Reveal Clonal Evolution and Gene Regulatory Networks in Relapsed and Refractory Multiple Myeloma.

This study attempted to investigate how clonal structure evolves, along with potential regulatory networks, as a result of multiline therapies in relapsed/refractory multiple myeloma (RRMM). Eight whole exome sequencing (WES) and one single cell RNA sequencing (scRNA-seq) were performed in order to assess dynamic genomic changes in temporal consecutive samples of one RRMM patient from the time of diagnosis to death (about 37 months). The 63-year-old female patient who suffered from MM (P1) had disease progression (PD) nine times from July 2017 [newly diagnosed (ND)] to Aug 2020 (death), and the force to drive branching-pattern evolution of malignant PCs was found to be sustained. The mutant-allele tumor heterogeneity (MATH) and tumor mutation burden (TMB) initially exhibited a downward trend, which was then upward throughout the course of the disease. Various somatic single nucleotide variants (SNVs) that had disappeared after the previous treatment were observed to reappear in later stages. Chromosomal instability (CIN) and homologous recombination deficiency (HRD) scores were observed to be increased during periods of all progression, especially in the period of extramedullary plasmacytoma. Finally, in combination with WES and scRNA-seq of P1-PD9 (the nineth PD), the intro-heterogeneity and gene regulatory networks of MM cells were deciphered. As verified by the overall survival of MM patients in the MMRF CoMMpass and GSE24080 datasets, RUNX3 was identified as a potential driver for RRMM.

High Expression of Succinate Dehydrogenase Subunit A Which Is Regulated by Histone Acetylation, Acts as a Good Prognostic Factor of Multiple Myeloma Patients.

Most patients with multiple myeloma (MM) will eventually relapse and current treatments have limited effect. Herein, we demonstrate that succinate dehydrogenase subunit A (SDHA) was low expressed in MM patients, and patients with SDHA relatively high expression had long overall survival and progression-free survival. Furthermore, SDHA high expression inhibited proliferation and invasion in MM cell lines and enhanced the anti-tumor and synergistic effect of chemotherapeutics. More importantly, chidamide was proved effective in MM by targeting SDHA, and expression of SDHA was increased by chidamide through acetylating H3K27 site of SDHA. Collectively, high expression of SDHA, which was regulated by histone acetylation and targeted by chidamide, might become a good prognostic factor of MM patients.

Globular C1q Receptor (gC1qR/p32/HABP1) Suppresses the Tumor-Inhibiting Role of C1q and Promotes Tumor Proliferation in 1q21-Amplified Multiple Myeloma.

Immunodeficiencies are widely becoming known as important features of multiple myeloma (MM) and may promote the proliferation of malignant cells as well as confer resistance to therapy. Few studies focus on the immunomodulatory effects of the complement system on MM. This study aims to explore the role of C1q in MM patients. Plasma C1q was found to be significantly reduced in MM patients, and the amount of C1q deposited around the CD138+ cells in bone marrow (BM) biopsy sections was observed to be much higher, especially in the subgroup with 1q21 amplification (Amp1q21). CD138+ cells expressed higher levels of C1q receptors (C1qRs) than CD138- cells. Patients with Amp1q21 expressed higher levels of globular C1qR (gC1qR), whereas patients without Amp21 expressed higher levels of collagen tail C1qR (cC1qR). Additionally, gC1qR was noted to suppress the MM-inhibiting role of C1q in H929, U266, and MM1S. gC1qR interacts with insulin-like growth factor 2 mRNA binding protein 3 (IGF2BP3), which also suppressed the function of C1q and regulated CDC28 protein kinase regulatory subunit 1B (CKS1B) mRNA. In summary, gC1qR suppressed the MM-inhibiting role of C1q and regulated CKS1B mRNA in promoting tumor proliferation via IGF2BP3 in 1q21-amplified MM. Our findings provide novel evidence on how MM cells evade the immune system and promote survival as well as suggest possible novel targets for future therapies of MM.

ZHX2 mediates proteasome inhibitor resistance via regulating nuclear translocation of NF-κB in multiple myeloma.

BACKGROUND: Multiple myeloma (MM) is an incurable hematological malignancy. Although proteasome inhibitors and immunomodulators have significantly improved patient outcomes, some patients respond poorly to treatment and almost all patients will relapse. Mechanisms of proteasome inhibitor resistance in multiple myeloma have not been fully elucidated. ZHX2 is a transcription regulator degraded via proteasome and presents both oncogenic or tumor suppressive effect in different cancers, however, it is still unknown that the role of ZHX2 in myeloma. In this study, we aim to demonstrate the effect and mechanism of ZHX2 on proteasome inhibitor resistance in MM. METHODS: GSE24080 gene expression profile datasets from Gene Expression Omnibus (GEO) were analyzed to evaluate the relationship between ZHX2 expression level and survival in MM. Expression of ZHX2 in human MM cell lines at baseline and after bortezomib (BTZ) treatment was determined by Western blotting (WB). The proliferation and apoptosis rate of MM cells treated with BTZ after the knockdown of ZHX2 were analyzed by flow cytometry. Nuclear translocation of NF-κB after the knockdown of ZHX2 was evaluated by WB and immunofluorescence, and the expression of NF-κB target genes was measured by real-time quantitative PCR. Co-immunoprecipitation (Co-IP) and WB were used to detect the interaction of ZHX2 with NF-κB. RESULTS: We found that higher ZHX2 expression was correlated with poorer clinical outcomes of patients. In addition, ZHX2 expression was relatively higher in RPMI-8226 and MM.1S cell lines and the level of ZHX2 protein was upregulated after BTZ treatment. Knockdown of ZHX2 significantly enhanced the sensitivity of MM cells to BTZ, inhibited nuclear translocation of NF-κB, and reduced mRNA expression of NF-κB target genes. It was also revealed that ZHX2 directly binds to NF-κB. CONCLUSION: Our study showed that ZHX2 can promote proteasome inhibitor resistance in MM cells by regulating the nuclear translocation of NF-κB.

Suppression of CXCL-1 Could Restore Necroptotic Pathway in Chronic Lymphocytic Leukemia.

PURPOSE: To clarify the role of different cytokines and selenite in the defective necroptotic pathway of chronic lymphocytic leukemia (CLL). PATIENTS AND METHODS: We randomly collected the peripheral blood samples of 11 untreated CLL patients and 10 healthy volunteers, and then separated B lymphocytes from peripheral blood. Then, real-time polymerase chain reaction (PCR), enzyme-linked immunosorbent assay (ELISA) and Western Blot were performed to detect the expression of different cytokines, including CXC-motif chemokine ligand 1 (CXCL-1). Finally, we used flow cytometry to analyze the percentage of surviving cells to figure out whether CLL cells or normal B lymphocytes underwent necroptosis. RESULTS: 1) The high expression of CXCL-1 was seen in CLL cells compared with normal B lymphocytes (p = 0.0001, adjusted p =0.0012); 2) The downregulation of CXCL-1 was shown in normal B lymphocytes after induction by TNF-α and z-VAD; 3) CLL cells could restore necroptosis induced by TNF-α and z-VAD after knockdown of CXCL-1; 4) The transcriptional and translational expression of LEF-1 were downregulated after the knockdown of CXCL-1 in CLL cells; 5. 3.2µM selenite could help CLL cells restore necroptosis (p = 0.0102) and inhibit the transcriptional and translational expression of CXCL-1. CONCLUSION: CXCL-1 played an important role in the defective necroptosis of CLL cells and regulated the expression of LEF-1. Selenite could inhibit the expression of CXCL-1 and help CLL cells restore necroptosis together with TNF-α and z-VAD. Selenite might be the potential medication of CLL in the future.

High expression of AMPD2 and obesity are associated with poor prognosis in colorectal cancer.

The protein-coding gene adenosine monophosphate deaminase (AMPD) 2 plays a critical role in energy metabolism by converting adenosine-5-monophosphate (AMP) to iosine inosine-5-monophosphate (IMP). Obesity affects metabolic abnormalities in tumor cells and has been associated with high expression levels of AMPD2 and colorectal cancer (CRC). In this study, we performed immunohistochemical analysis of AMPD2 expression in 158 patients with CRC. Quantitative real-time polymerase chain reaction (qRT-PCR) was performed to determine AMPD2 mRNA expression levels, which were validated by The Cancer Genome Atlas (TCGA) datasets. Chi-square test and Fisher's exact test were used to evaluate the correlation between the expression of AMPD2 and clinicopathological parameters of CRC. Overall survival (OS) rates of the CRC patients were calculated using Kaplan-Meier survival analysis and a Cox proportional regression model was performed for univariate and multivariate analysis. A logistic regression model was used to plot the receiver operating characteristic (ROC) curve and to evaluate the predictive effect of multivariate studies on prognosis outcomes of CRC. We found a significant increase in AMPD2 expression in tumor tissue (91.8%, 146/158) compared to adjacent normal tissue (52.5%, 83/158, P < 0.01). The positive rate of AMPD2 expression was 72.7% (39/54) in overweight individuals versus 51.9% (54/104) in individuals with a normal weight (P = 0.014). AMPD2 mRNA levels as determined by qRT-PCR elevated levels of AMPD2 transcripts were higher in CRC samples compared to adjacent normal tissues (P < 0.05). In both the TCGA colon adenocarcinoma and rectal adenocarcinoma dataset, the number of CRC patients with increased levels of AMPD2 in tumor tissues was significantly higher compared to patients with adjacent normal tissue (P < 0.001). High expression of AMPD2 was associated with TNM stage, higher histological grade, obesity, and lower OS rates in patients with CRC. Obesity and high expression of AMPD2 in patients are with poor prognosis. Moreover, multivariate analysis indicated that AMPD2 levels and TNM stage were significant independent prognostic factors in CRC patients. The logistic regression predictive effect of the area under the curve (AUC) was 0.821 (P < 0.001). In conclusion, high levels of AMPD2 and obesity are associated with poor prognosis in patients with CRC.

[Diagnostic value of hepatobiliary phase imaging with GD-EOB-DTPA for hepatocellular carcinomas in cirrhosis].

OBJECTIVE: To assess the diagnostic value of hepatobiliary phase imaging with GD-EOB-DTPA for hepatocellular carcinomas (HCC) in cirrhosis. METHODS: A total of 43 cirrhotic patients with 45 HCC lesions underwent the examinations of T2WI, DWI, T1WI in-phase and opposed-phase and dynamic contrast enhancement and hepatobiliary phase. Two separate analyses of imaging set with and without hepatobiliary phase images were performed. The confidence scores for HCC diagnosis, consistency, area under the receiver operating characteristic (ROC) curve and sensitivity and positive predictive values of two observers were compared. RESULTS: After adding hepatobiliary phase, there was a significant increase of confidence scores in diagnosing HCC by both observers (P < 0.05) and the consistency of two observers also increased. The area under the ROC curve improved by both observers, but no significant differences were detected (P > 0.05). The sensitivity increased significantly (P < 0.05) and no significant differences were observed for the positive predictive values by both observers (P > 0.05). CONCLUSION: Hepatobiliary phase imaging may improve the diagnostic confidence and sensitivity of GD-EOB-DTPA for HCC in cirrhosis.