Multivariate analysis of prognostic factors in patients with lip squamous cell carcinoma after surgery.

BACKGROUND: Lip squamous cell carcinoma (LSCC) was one of the most common cancer types of head and neck tumors. This study aimed to find more predictors of the prognosis in postoperative LSCC patients. METHODS: A total of 147 LSCC patients between June 2012 and June 2018 were collected from two tertiary care institutions. There were 21 clinicopathological factors included and analyzed in our study. The univariate and multivariate Cox regression analyses were performed to find the independent prognostic factors for predicting progression-free survival (PFS) and overall survival (OS) in postoperative LSCC patients. The role of adjuvant radiotherapy in various subgroups was displayed by Kaplan-Meier plots. RESULTS: The 1-, 3-, and 5-year PFS of postoperative LSCC patients were 88.4%, 70.1%, and 57.8%, respectively. Similarly, the 1-, 3-, and 5-year OS of postoperative LSCC patients were 94.6%, 76.9%, and 69.4%, respectively. The results suggested that postoperative LSCC patients with age at diagnosis ≥ 70 years, grade with moderate or poor differentiate, the American Joint Committee on Cancer (AJCC) stage IV, higher systemic immune-inflammation index (SII), surgical margin < 5, and age-adjusted Charlson Comorbidity Index (ACCI) ≥ 5 tend to have a poorer PFS (all P < 0.05). Besides, postoperative LSCC patients with age at diagnosis ≥ 70 years, AJCC stage IV, higher GPS, higher SII, and ACCI ≥ 5 tend to have a worse OS (all P < 0.05). Additionally, postoperative patients with LSCC in the subgroup of ACCI < 5 and AJCC III-IV stage was more likely to benefit from adjuvant radiotherapy, but not for the other subgroups. CONCLUSION: We identified a series of significant immune-inflammation-related and comorbidity-related clinicopathological factors associated with the prognosis of postoperative LSCC patients by local data from two tertiary care institutions in China, which can be helpful for patients and surgeons to pay more attention to nutrition, inflammation, and complications and finally obtained a better prognosis.

Nomogram for predicting the preoperative lymph node metastasis in resectable pancreatic cancer.

BACKGROUND: Lymph node metastasis (LNM) is a critical prognostic factor in resectable pancreatic cancer (PC) patients, determining treatment strategies. This study aimed to develop a clinical model to adequately and accurately predict the risk of LNM in PC patients. METHODS: 13,200 resectable PC patients were enrolled from the SEER (Surveillance, Epidemiology, and End Results) database, and randomly divided into a training group and an internal validation group at a ratio of 7:3. An independent group (n = 62) obtained from The First Affiliated Hospital of Xinxiang Medical University was enrolled as the external validation group. The univariate and multivariate logistic regression analyses were used to screen independent risk factors for LNM. The minimum Akaike's information criterion (AIC) was performed to select the optimal model parameters and construct a nomogram for assessing the risk of LNM. The performance of the nomogram was assessed by the receiver operating characteristics (ROC) curve, calibration plot, and decision curve analysis (DCA). In addition, an online web calculator was designed to assess the risk of LNM. RESULT: A total of six risk predictors (including age at diagnosis, race, primary site, grade, histology, and T-stage) were identified and included in the nomogram. The areas under the curves (AUCs) [95% confidential interval (CI)] were 0.711 (95%CI: 0.700-0.722), 0.700 (95%CI: 0.683-0.717), and 0.845 (95%CI: 0.749-0.942) in the training, internal validation and external validation groups, respectively. The calibration curves showed satisfied consistency between nomogram-predicted LNM and actual observed LNM. The concordance indexes (C-indexes) in the training, internal, and external validation sets were 0.689, 0.686, and 0.752, respectively. The DCA curves of the nomogram demonstrated good clinical utility. CONCLUSION: We constructed a nomogram model for predicting LNM in pancreatic cancer patients, which may help oncologists and surgeons to choose more individualized clinical treatment strategies and make better clinical decisions.

Nomograms for predicting overall survival and cancer-specific survival in elderly patients with epithelial ovarian cancer.

BACKGROUND: Epithelial ovarian cancer (EOC) is one of the most fatal gynecological malignancies among elderly patients. We aim to construct two nomograms to predict the overall survival (OS) and cancer-specific survival (CSS) in elderly EOC patients. METHODS: Elderly patients with EOC between 2000 and 2019 were selected from the Surveillance, Epidemiology, and End Results (SEER) database. Enrolled patients were randomly divided into the training and validation set at a ratio of 2:1. The OS and CSS were recognized as endpoint times. The independent prognostic factors from the multivariate analysis were used to establish nomograms for predicting the 3-, 5- and 10-year OS and CSS of elderly EOC patients. The improvement of predictive ability and clinical benefits were evaluated by consistency index (C-index), receiver operating characteristic (ROC), calibration curve, decision curve (DCA), net reclassification improvement (NRI), and integrated discrimination improvement (IDI). Finally, the treatment efficacy of surgery and chemotherapy in low-, medium-, and high-risk groups were displayed by Kaplan-Meier curves. RESULTS: Five thousand five hundred eighty-eight elderly EOC patients were obtained and randomly assigned to the training set (n = 3724) and validation set (n = 1864). The independent prognostic factors were utilized to construct nomograms for OS and CSS. Dynamic nomograms were also developed. The C-index of the OS nomogram and CSS nomogram were 0.713 and 0.729 in the training cohort. In the validation cohort, the C-index of the OS nomogram and CSS nomogram were 0.751 and 0.702. The calibration curve demonstrated good concordance between the predicted survival rates and actual observations. Moreover, the NRI, IDI, and DCA curves determined the outperformance of the nomogram compared with the AJCC stage system. Besides, local tumor resection had a higher benefit on the prognosis in all patients. Chemotherapy had a better prognosis in the high-risk groups, but not for the medium- risk and low-risk groups. CONCLUSIONS: We developed and validated nomograms for predicting OS and CSS in elderly EOC patients to help gynecologists to develop an appropriate individualized therapeutic schedule.

Autophagy-related protein expression was associated with BRAF V600E mutation in epilepsy associated glioneuronal tumors.

PURPOSE: The aim of this study was to explore the expression level of autophagy-related proteins in epileptic patients with glioneuronal tumors (GNTs) and evaluate the association with clinicopathological features. MATERIALS AND METHODS: We obtained the brain specimens from 33 patients with GNTs, including 22 gangliogliomas (GGs) and 11 dysembryoplastic neuroepithelial tumors (DNTs). The expression of two autophagy-related proteins (LC3B and Beclin-1) was evaluated by immunohistochemistry, and BRAF V600E mutation was examined by DNA sequencing. RESULTS: Among 33 epileptic patients with GNTs, the frequency of high expression of LC3B was 36.4% (12/33), and that of Beclin-1 was 39.4% (13/33). High expression of LC3B and Beclin-1 proteins was significantly associated with BRAF V600E mutation in GNTs (P=0.008; P=0.018), and LC3B overexpression was also correlated with temporal location of GNTs (P=0.002). In GGs alone, high expression of LC3B revealed significant correlation with BRAF V600E mutation and temporal location (P=0.020; P=0.015), while Beclin-1 showed no correlation with them (P>0.05). Furthermore, autophagy-related proteins did not show any association with other studied clinicopathological features, such as gender, age at seizure onset, epilepsy duration and postoperative seizure outcome. CONCLUSIONS: Our observations demonstrated that impaired autophagy may be associated with BRAF V600E mutation. However, large sample studies with long-term follow-up were required.

Binding Behaviors for Different Types of DNA G-Quadruplexes: Enantiomers of [Ru(bpy)2(L)](2+) (L=dppz, dppz-idzo).

Polymorphic DNA G-quadruplex recognition has attracted great interest in recent years. The strong binding affinity and potential enantioselectivity of chiral [Ru(bpy)2 (L)](2+) (L=dipyrido[3,2-a:2',3'-c]phenazine, dppz-10,11-imidazolone; bpy=2,2'-bipyridine) prompted this investigation as to whether the two enantiomers, Δ and Λ, can show different effects on diverse structures with a range of parallel, antiparallel and mixed parallel/antiparallel G-quadruplexes. These studies provide a striking example of chiral-selective recognition of DNA G-quadruplexes. As for antiparallel (tel-Na(+)) basket G-quadruplex, the Λ enantiomers bind stronger than the Δ enantiomers. Moreover, the behavior reported here for both enantiomers stands in sharp contrast to B-DNA binding. The chiral selectivity toward mixed parallel/antiparallel (tel-K(+)) G-quadruplex of both compounds is weak. Different loop arrangements can change chiral complex selectivity for both antiparallel and mixed parallel/antiparallel G-quadruplex. Whereas both Δ and Λ isomers bind to parallel G-quadruplexes with comparable affinity, no appreciable stereoselective G-quadruplex binding of the isomers was observed. In addition, different binding stoichiometries and binding modes for Δ and Λ enantiomers were confirmed. The results presented here indicate that chiral selective G-quadruplex binding is not only related to G-quadruplex topology, but also to the sequence and the loop constitution.

Role of Wnt Inhibitory Factor-1 in Inhibition of Bisdemethoxycurcumin Mediated Epithelial-to-Mesenchymal Transition in Highly Metastatic Lung Cancer 95D Cells.

BACKGROUND: Bisdemethoxycurcumin (BDMC) is an active component of curcumin and a chemotherapeutic agent, which has been suggested to inhibit tumor growth, invasion and metastasis in multiple cancers. But its contribution and mechanism of action in invasion and metastasis of non-small cell lung cancer (NSCLC) are not very clear. Therefore, we tried to study the effects of BDMC on regulation of epithelial-to-mesenchymal transition (EMT), which is closely linked to tumor cell invasion and metastasis. METHODS: In this study, we first induced transforming growth factor-ß1 (TGF-ß1) mediated EMT in highly metastatic lung cancer 95D cells. Thereafter, we studied the effects of BDMC on invasion and migration of 95D cells. In addition, EMT markers expressions were also analyzed by western blot and immunofluorescence assays. The contribution of Wnt inhibitory factor-1 (WIF-1) in regulating BDMC effects on TGF-ß1 induced EMT were further analyzed by its overexpression and small interfering RNA knockdown studies. RESULTS: It was observed that BDMC inhibited the TGF-ß1 induced EMT in 95D cells. Furthermore, it also inhibited the Wnt signaling pathway by upregulating WIF-1 protein expression. In addition, WIF-1 manipulation studies further revealed that WIF-1 is a central molecule mediating BDMC response towards TGF-ß1 induced EMT by regulating cell invasion and migration. CONCLUSIONS: Our study concluded that BDMC effects on TGF-ß1 induced EMT in NSCLC are mediated through WIF-1 and elucidated a novel mechanism of EMT regulation by BDMC.

Autophagy Accompanied with Bisdemethoxycurcumin-induced Apoptosis in Non-small Cell Lung Cancer Cells.

OBJECTIVE: To investigate the effects of bisdemethoxycurcumin (BDMC) on non-small cell lung cancer (NSCLC) cell line, A549, and the highly metastatic lung cancer 95D cells. METHODS: CCK-8 assay was used to assess the effect of BDMC on cytotoxicity. Flow cytometry was used to evaluate apoptosis. Western blot analysis, electron microscopy, and quantification of GFP-LC3 punctuates were used to test the effect of BDMC on autophagy and apoptosis of lung cancer cells. RESULTS: BDMC inhibited the viability of NSCLC cells, but had no cytotoxic effects on lung small airway epithelial cells (SAECs). The apoptotic cell death induced by BDMC was accompanied with the induction of autophagy in NSCLC cells. Blockage of autophagy by the autophagy inhibitor 3-methyladenine (3-MA) repressed the growth inhibitory effects and induction of apoptosis by BDMC. In addition, BDMC treatment significantly decreased smoothened (SMO) and the transcription factor glioma-associated oncogene 1 (Gli1) expression. Furthermore, depletion of Gli1 by siRNA and cyclopamine (a specific SMO inhibitor) induced autophagy. CONCLUSION: Aberrant activation of Hedgehog (Hh) signaling has been implicated in several human cancers, including lung cancers. The present findings provide direct evidence that BDMC-induced autophagy plays a pro-death role in NSCLC, in part, by inhibiting Hedgehog signaling.