Integrating DOI in T classification improves the predictive performance of laryngeal cancer staging

It has been recognized that depth of invasion (DOI) is closely associated with patient survival for most types of cancer. The purpose of this study was to determine the DOI optimal cutoff value and its prognostic value in laryngeal squamous carcinoma (LSCC). Most importantly, we evaluated the prognostic performance of five candidate modified T-classification models in patients with LSCC. LSCC patients from Harbin Medical University Cancer Hospital and Chinese Academy of Medical Sciences Cancer Hospital were divided into training group (n = 412) and validation group (n = 147). The primary outcomes were overall survival (OS) and relapse-free survival (RFS), and the effect of DOI on prognosis was analyzed using a multivariable regression model. We identified the optimal model based on its simplicity, goodness of fit and Harrell's consistency index. Further independent testing was performed on the external validation queue. The nomograms was constructed to predict an individual's OS rate at one, three, and five years. In multivariate analysis, we found significant associations between DOI and OS (Depth of Medium-risk invasion HR, 2.631; P < .001. Depth of high-risk invasion: HR, 5.287; P < .001) and RFS (Depth of high-risk invasion: HR, 1.937; P = .016). Model 4 outperformed the American Joint Committee on Cancer (AJCC) staging system based on a low Akaike information criterion score, improvement in the concordance index, and Kaplan-Meier curves. Inclusion of DOI in the current AJCC staging system can improve the differentiation of T classification in LSCC patients.

TAGET: a toolkit for analyzing full-length transcripts from long-read sequencing

Single-molecule Real-time Isoform Sequencing (Iso-seq) of transcriptomes by PacBio can generate very long and accurate reads, thus providing an ideal platform for full-length transcriptome analysis. We present an integrated computational toolkit named TAGET for Iso-seq full-length transcript data analyses, including transcript alignment, annotation, gene fusion detection, and quantification analyses such as differential expression gene analysis and differential isoform usage analysis. We evaluate the performance of TAGET using a public Iso-seq dataset and newly sequenced Iso-seq datasets from tumor patients. TAGET gives significantly more precise novel splice site prediction and enables more accurate novel isoform and gene fusion discoveries, as validated by experimental validations and comparisons with RNA-seq data. We identify and experimentally validate a differential isoform usage gene ECM1, and further show that its isoform ECM1b may be a tumor-suppressor in laryngocarcinoma. Our results demonstrate that TAGET provides a valuable computational toolkit and can be applied to many full-length transcriptome studies.

Magnetic hydrogel particles improve nanopore sequencing of SARS-CoV-2 and other respiratory viruses

Presented here is a magnetic hydrogel particle enabled workflow for capturing and concentrating SARS-CoV-2 from diagnostic remnant swab samples that significantly improves sequencing results using the Oxford Nanopore Technologies MinION sequencing platform. Our approach utilizes a novel affinity-based magnetic hydrogel particle, circumventing low input sample volumes and allowing for both rapid manual and automated high throughput workflows that are compatible with Nanopore sequencing. This approach enhances standard RNA extraction protocols, providing up to 40 × improvements in viral mapped reads, and improves sequencing coverage by 20-80% from lower titer diagnostic remnant samples. Furthermore, we demonstrate that this approach works for contrived influenza virus and respiratory syncytial virus samples, suggesting that it can be used to identify and improve sequencing results of multiple viruses in VTM samples. These methods can be performed manually or on a KingFisher automation platform.

Effect of regulatory cell death on the occurrence and development of head and neck squamous cell carcinoma

Head and neck cancer is a malignant tumour with a high mortality rate characterized by late diagnosis, high recurrence and metastasis rates, and poor prognosis. Head and neck squamous cell carcinoma (HNSCC) is the most common type of head and neck cancer. Various factors are involved in the occurrence and development of HNSCC, including external inflammatory stimuli and oncogenic viral infections. In recent years, studies on the regulation of cell death have provided new insights into the biology and therapeutic response of HNSCC, such as apoptosis, necroptosis, pyroptosis, autophagy, ferroptosis, and recently the newly discovered cuproptosis. We explored how various cell deaths act as a unique defence mechanism against cancer emergence and how they can be exploited to inhibit tumorigenesis and progression, thus introducing regulatory cell death (RCD) as a novel strategy for tumour therapy. In contrast to accidental cell death, RCD is controlled by specific signal transduction pathways, including TP53 signalling, KRAS signalling, NOTCH signalling, hypoxia signalling, and metabolic reprogramming. In this review, we describe the molecular mechanisms of nonapoptotic RCD and its relationship to HNSCC and discuss the crosstalk between relevant signalling pathways in HNSCC cells. We also highlight novel approaches to tumour elimination through RCD.

Nomogram Model Based on Iodine Nutrition and Clinical Characteristics of Papillary Thyroid Carcinoma to Predict Lateral Lymph Node Metastasis

OBJECTIVE

Preoperative evaluation of lateral lymph node metastasis (LLNM) in patients with papillary thyroid carcinoma (PTC) has been one of the major clinical challenges. This study aims to develop and validate iodine nutrition-related nomogram models to predict lateral cervical lymph node metastasis in patients with PTC.

METHODS

This is a retrospective study. Urinary iodine concentration (UIC) and serum iodine concentration (SIC) were measured in 187 LLNM patients and 289 non-LLNM (NLLNM) patients. All patients were randomized 3:1 into the training cohort (n = 355) and the validation cohort (n = 121). Using logistic regression analysis, we analyzed the influence of iodine nutrition-related factors and clinicopathological characteristics on LLNM in PTC patients. Lasso regression method was used to screen risk factors and construct a nomogram for predicting LLNM. The receiver operating characteristic curve (ROC curve), calibration curve, and decision curve analysis (DCA) of the nomogram models were carried out for the training and validation cohorts.

RESULTS

Gender, SIC, smoking history, drinking history, family history of PTC, multifocality, bilateral or unilateral tumors, TSH, Tg, and tumor size were included in the nomogram model predicting LLNM, with an area under the curve (AUC) of .795. The nomogram model showed good calibration and clinical benefit in both the training and validation cohorts.

CONCLUSION

The nomogram model based on iodine nutrition and other clinicopathological features is effective for predicting the lateral lymph node metastasis in PTC patients.

Heterogeneity in the onwards transmission risk between local and imported cases affects practical estimates of the time-dependent reproduction number

During infectious disease outbreaks, inference of summary statistics characterizing transmission is essential for planning interventions. An important metric is the time-dependent reproduction number (Rt), which represents the expected number of secondary cases generated by each infected individual over the course of their infectious period. The value of Rt varies during an outbreak due to factors such as varying population immunity and changes to interventions, including those that affect individuals' contact networks. While it is possible to estimate a single population-wide Rt, this may belie differences in transmission between subgroups within the population. Here, we explore the effects of this heterogeneity on Rt estimates. Specifically, we consider two groups of infected hosts: those infected outside the local population (imported cases), and those infected locally (local cases). We use a Bayesian approach to estimate Rt, made available for others to use via an online tool, that accounts for differences in the onwards transmission risk from individuals in these groups. Using COVID-19 data from different regions worldwide, we show that different assumptions about the relative transmission risk between imported and local cases affect Rt estimates significantly, with implications for interventions. This highlights the need to collect data during outbreaks describing heterogeneities in transmission between different infected hosts, and to account for these heterogeneities in methods used to estimate Rt. This article is part of the theme issue 'Technical challenges of modelling real-life epidemics and examples of overcoming these'.

Emerging roles of platelets in cancer biology and their potential as therapeutic targets

The main role of platelets is to control bleeding and repair vascular damage via thrombosis. They have also been implicated to promote tumor metastasis through platelet-tumor cell interactions. Platelet-tumor cell interactions promote tumor cell survival and dissemination in blood circulation. Tumor cells are known to induce platelet activation and alter platelet RNA profiles. Liquid biopsies based on tumor-educated platelet biomarkers can detect tumors and correlate with prognosis, personalized therapy, treatment monitoring, and recurrence prediction. Platelet-based strategies for cancer prevention and tumor-targeted therapy include developing drugs that target platelet receptors, interfere with the release of platelet particles, inhibit platelet-specific enzymes, and utilize platelet-derived “nano-platelets” as a targeted drug delivery platform for tumor therapy. This review elaborates on platelet-tumor cell interactions and the molecular mechanisms and discusses future research directions for platelet-based liquid biopsy techniques and platelet-targeted anti-tumor strategies.

[Suppression of HMGB1 inhibits neuronal autophagy and apoptosis to improve neurological deficits in rats following intracerebral hemorrhage]

OBJECTIVE

To investigate the effect of suppressing high-mobility group box 1 (HMGB1) on neuronal autophagy and apoptosis in rats after intracerebral hemorrhage (ICH) in rats.

METHODS

Rat models of ICH induced by intracerebral striatum injection of 0.2 U/mL collagenase Ⅳ were treated with 1 mg/kg anti-HMGB1 mAb or a control anti-IgG mAb injected via the tail immediately and at 6 h after the operation (n=5). The rats in the sham-operated group (with intracranial injection of 2 μL normal saline) and ICH model group (n=5) were treated with PBS in the same manner after the operation. The neurological deficits of the rats were evaluated using modified neurological severity score (mNSS). TUNEL staining was used to detect apoptosis of the striatal neurons, and the expressions of HMGB1, autophagy-related proteins (Beclin-1, LC3-Ⅱ and LC3-Ⅰ) and apoptosis-related proteins (Bcl-2, Bax and cleaved caspase-3) in the brain tissues surrounding the hematoma were detected using Western blotting. The expression of HMGB1 in the striatum was detected by immunohistochemistry, and serum level of HMGB1 was detected with ELISA.

RESULTS

The rat models of ICH showed significantly increased mNSS (P < 0.05), which was markedly lowered after treatment with anti- HMGB1 mAb (P < 0.05). ICH caused a significant increase of apoptosis of the striatal neurons (P < 0.05), enhanced the expressions of beclin-1, LC3-Ⅱ, Bax and cleaved caspase-3 (P < 0.05), lowered the expressions of LC3-Ⅰ and Bcl-2 (P < 0.05), and increased the content of HMGB1 (P < 0.05). Treatment with anti-HMGB1 mAb obviously lowered the apoptosis rate of the striatal neurons (P < 0.05), decreased the expressions of Beclin-1, LC3-Ⅱ, Bax and cleaved caspase-3 (P < 0.05), increased the expressions of LC3-Ⅰ and Bcl-2 (P < 0.05), and reduced the content of HMGB1 in ICH rats (P < 0.05).

CONCLUSION

Down- regulation of HMGB1 by anti-HMGB1 improves neurological functions of rats after ICH possibly by inhibiting autophagy and apoptosis of the neurons.

[Clinical analysis of penetrating keratoplasty for infants with congenital corneal opacity]

Objective: To investigate the corneal graft survival and related risk factors of primary penetrating keratoplasty in congenital corneal opacity infants. Methods: It was a retrospective cohort study. Data were collected from forty-two infants (51 eyes) who were aged ≤12 months and diagnosed with congenital corneal opacity in Beijing Tongren Hospital and Beijing Anzhen Hospital from January 1, 2017 to January 31, 2018. The mean age at surgery was (5.7±2.2) months (3-12 months). The mean follow-up duration was (28.6±2.6) months (24-33 months). All the patients underwent penetrating keratoplasty. The status of the corneal grafts and complications were observed and recorded during the regular follow-up. The survival probabilities were estimated by using the Kaplan-Meier and Log-rank test. The graft survival between different influence factors was analyzed by using the χ² test. Results: The Kaplan-Meier survival rates for penetrating keratoplasty were 84.3% (43/51) at 6 months, 78.4% (40/51) at 12 months and 60.8% (31/51) at the last follow-up. The presence of corneal neovascularization was significantly correlated with graft failure (χ²=5.264, P=0.022). The graft survival differed between eyes receiving combined surgery and mere penetrating keratoplasty and in eyes with varied surgical indications (P=0.039, <0.01). Increased intraocular pressure (7 eyes, 13.7%) and persistent epithelial defects (7 eyes, 13.7%) were the most common postoperative complications, followed by complicated cataract (4 eyes, 7.8%) and posterior capsule opacification (2 eyes, 3.9%). Conclusions: The graft survival rate was satisfactory following pediatric keratoplasty although it had a tendency to decrease with the follow-up time. Corneal neovascularization was a major risk factor of graft failure. Surgical indications and procedures also had a certain effect on the graft survival.

AB0864 A nomogram model combining inflammatory factors and MRI radiomics to assess the disease activity of the patients with axSpA in a prospective study

Background

Clinical and magnetic resonance imaging (MRI) disease activity score (DAS) are measuring different aspects of axial spondyloarthritis (axSpA), they are essential in disease activity assessment. The radiomics was on facilitating readings by clinical specialists via enhancing the medical images in which subtle data differences could be distinguished.

Objectives

If the additional information of MRI imaging can be considered as a predictor for axSpA disease activity? In this study, we sought to construct a nomogram integrating the sacroiliac joint (SIJ)- MRI radiomics features and the inflammatory biomarkers to assess disease activity and compare it with clinical disease acitivity index in axSpA patients.

Methods

203 patients data were collected prospectively and confirmed as axSpA were randomly divided into training (n = 143) and validation cohorts (n = 60). 1316 radiomics features were extracted from the 3.0T SIJ-MRI. A Nomogram model was constructed using multivariate logistic regression analysis Incorporating independent clinical factors and radiomics features score (Rad-score). The performance of clinics, Rad-score and nomogram models were evaluated by ROC analysis, calibration curve and decision curve analysis (DCA), and compared with the disease activity index(Ankylosing Spondylitis DAS (ASDAS)-C reactive protein (CRP), ASDAS-erythrocyte sedimentation rate (ESR), Bath Ankylosing Spondylitis Disease Activity Index (BASDAI), Bath Ankylosing Spondylitis Functional Index (BASFI)) and Spondyloarthritis Research Consortium of Canada (SPARCC) MRI scoring system.

Results

The Rad-score allowed a good discrimination in the training (AUC, 0.91; 95% CI, 0.85-0.96) and the validation cohort (AUC, 0.84; 95% CI, 0.73-0.96). The CRP-radiomics nomogram model also showed favorable discrimination in the training (AUC, 0.96; 95% CI, 0.93-0.99) and the validation cohort (AUC, 0.89; 95% CI, 0.80-0.98), better than BASDAI(AUC, 0.58), ASDAS-CRP(AUC, 0.72), ASDAS-ESR(AUC, 0.77), ESR(AUC, 0.72), CRP(AUC, 0.77) and BASFI(AUC, 0.73), had no statistical difference with SPARCC(AUC, 0.87). Calibration curves and DCA demonstrated the nomogram fit well (p > 0.05) and was useful for activity evaluation.

Conclusion

Rad-score showed good discriminative ability to assess disease activity in axSpA. The nomogram can increase the efficacy for assessment axSpA disease activity, which might simplify clinical evaluation.

Figure 1.

Comparison of ROC curve analyses in prediction models. ROC curves of the clinical features (green curve), radiomics signature model (blue curve), and hybrid model (gold curve) of axSpA in the training cohort (A) and validation cohort (B), respectively. In addition, there are AUC of ASDAS-CRP(pink curve), ASDAS-ESR(brown curve), BASDAI(purple curve), BASFI(azure curve) and SPARCC scoring system(yellow curve) in the validation cohort (B), respectively. AUC: area under the curve; ROC: receiver operating characteristic; SPARCC: Spondyloarthritis Research Consortium of Canada; BASDAI: Bath Ankylosing Spondylitis Disease Activity Index; ASDAS: Ankylosing Spondylitis Disease Activity Score; CRP: C reactive protein; ESR: erythrocyte sedimentation rate; BASFI: Bath Ankylosing Spondylitis Disease Activity Index.

References

[1]Lee KH, Choi ST, Lee GY, Ha YJ, Choi SI. Method for Diagnosing the Bone Marrow Edema of Sacroiliac Joint in Patients with Axial Spondyloarthritis Using Magnetic Resonance Image Analysis Based on Deep Learning. Diagnostics (Basel). 2021;11(7).

[2]Zheng Q, Liu W, Huang Y, Gao Z, Wu Y, Wang X, et al. Predictive Value of Active Sacroiliitis in MRI for Flare Among Chinese Patients with Axial Spondyloarthritis in Remission. Rheumatol Ther. 2021;8(1):411-24.

Acknowledgements

No conflict of interest

Disclosure of Interests

None declared

POS0962 CAN RADIOMICS REPLACE SPARCC SCORING SYSTEM IN EVALUATING BONE MARROW OEDEMA OF THE SACROILIAC JOINTS IN AXIAL SPONDYLOARTHRITIS?

Background

Bone marrow oedema (BMO) of the sacroiliac joints (SIJs) is evaluated to diagnose, classify and monitor disease activity in patients with axial spondyloarthritis (axSpA). Available quantitative methodologies rely on human visual assessment, and errors can’t be completely avoided. Radiomics can extract and select discriminative and quantified features from regions of interest (ROIs), making a more accurate and objective description of BMO.

Objectives

To develop a more objective and efficient method based on radiomics to evaluate BMO of the SIJs by magnetic resonance imaging (MRI) in patients with axSpA in comparison with Spondyloarthritis Research Consortium of Canada (SPARCC) scoring system.

Methods

From September 2013 to July 2021, 523 patients with axSpA underwent 3.0T SIJ-MRI were included, who were randomly classified as training cohort(n=367) and validation cohort(n=156). The optimal radiomics features, selected from the 3.0T SIJ-MRI in the training cohort, were included to build the radiomics model. Four clinical risk predictors were adopted to build the clinical model. The performance of the clinical and radiomics models was evaluated by ROC analysis and decision curve analysis (DCA). Rad-scores were calculated by the radiomics model and SPARCC scores were performed to quantify the BMO of SIJs. We also assessed the correlation between Rad-score and SPARCC score.

Results

The radiomics model, built by 15 optimal features, showed favorable discrimination about SPARCC score <2 or ≥2 both in the training (AUC, 0.91; 95% CI: 0.88-0.94) and the validation cohort (AUC, 0.89; 95% CI, 0.84-0.94). DCA confirmed that the radiomics model was clinically useful. Furthermore, Rad-score has significant correlation with SPARCC score for scoring the status of BMO (rs=0.78, P< 0.001), and moderation correlation for scoring the change (r=0.40, P=0.005).

Conclusion

The radiomics can accurately assess the BMO of the SIJs in axSpA, providing an alternative to SPARCC scoring system. There was a positive correlation between Rad-score and SPARCC score.

References

[1]van der Heijde D, Sieper J, Maksymowych WP, Lambert RG, Chen S, Hojnik M, et al. Clinical and MRI remission in patients with nonradiographic axial spondyloarthritis who received long-term open-label adalimumab treatment: 3-year results of the ABILITY-1 trial. Arthritis Res Ther. 2018;20(1):61.

[2]Landewé RB, Hermann KG, van der Heijde DM, Baraliakos X, Jurik AG, Lambert RG, et al. Scoring sacroiliac joints by magnetic resonance imaging. A multiple-reader reliability experiment. The Journal of rheumatology. 2005;32(10):2050-5.

[3]Cereser L, Zabotti A, Zancan G, Quartuccio L, Cicciò C, Giovannini I, et al. Magnetic resonance imaging assessment of ASAS-defined active sacroiliitis in patients with inflammatory back pain and suspected axial spondyloarthritis: a study of reliability. Clinical and experimental rheumatology. 2021.

[4]Maksymowych WP, Inman RD, Salonen D, Dhillon SS, Williams M, Stone M, et al. Spondyloarthritis research Consortium of Canada magnetic resonance imaging index for assessment of sacroiliac joint inflammation in ankylosing spondylitis. Arthritis Rheum. 2005;53(5):703-9.

[5]Gillies RJ, Kinahan PE, Hricak H. Radiomics: Images Are More than Pictures, They Are Data. Radiology. 2016;278(2):563-77.

Table 1.

Rad-scores corresponding to different SPARCC score intervals about the status of SIJ-BMO.

SPARCC scorenRad-scoreMean(sd)Median (iqr)Range0-1170-1.31(1.64)-1.39(2.16)-6.46, 2.352-61250.73(1.86)0.62(2.12)-3.08, 8.487-11552.25(1.80)2.36(1.79)-1.17, 8.3612-16432.65(2.14)2.66(3.21)-0.76, 7.3917-21383.31(2.05)3.25(2.88)-0.88, 7.5522-26263.08(1.55)3.38(2.12)-1.00, 5.3827-31253.77(1.36)3.77(1.59)0.40, 6.27>31414.10(1.51)4.32(2.28)1.00, 6.96

Disclosure of Interests

None declared

Assessment of immune status of laryngeal squamous cell carcinoma can predict prognosis and guide treatment

BACKGROUND

In the past few years, immunotherapy has changed the way we treat solid tumors. People pay more and more attention to the immune microenvironment of laryngeal squamous cell carcinoma (LSCC). In this study, our immunotherapy research took advantage of the clinical database and focused our in-depth analysis on the tumor microenvironment (TME).

METHODS

This study evaluated the relationship between the clinical outcome and the local tissue and overall immune status in 412 patients with primary LSCC. We constructed and validated a risk model that could predict prognosis, assess immune status, identify high-risk patients, and develop personalized treatment plans through bioinformatics. In addition, through immunohistochemical analysis, we verified the differential expression of CTSL and KDM5D genes with the largest weight coefficients in the model in LSCC tissues and their influence on the prognosis and tumor-infiltrating lymphocytes (TILs).

RESULTS

We found that interstitial tumor-infiltrating lymphocytes, tumor parenchymal-infiltrating lymphocyte volume, tumor infiltrates lymphocytes of frontier invasion, and the platelet-to-lymphocyte ratio (PLR) were independent factors affecting the prognosis of patients with LSCC. A novel risk model can guide clinicians to accurately predict prognosis, identify high-risk patients, and formulate personalized treatment plans. The differential expression of genes such as CTSL and KDM5D has a significant correlation with the TILs of LSCC and the prognosis of patients.

CONCLUSION

Local and systemic inflammatory markers in patients with laryngeal squamous cell carcinoma are reliable prognostic factors. The risk model and CTSL, KDM5D gene have important potential research value.

Different Primary Sites of Hypopharyngeal Cancer Have Different Lymph Node Metastasis Patterns: A Retrospective Analysis From Multi-Center Data

Background

Most hypopharyngeal cancers (HPCs) develop lymph node metastasis (LNM) at initial diagnosis. Understanding the pattern of LNM in HPC could help both surgeons and radiologists make decisions in the management of cervical lymph nodes.

Methods

A total of 244 newly diagnosed HPC patients between January 2010 and December 2018 were recruited from three specialized cancer hospitals in mainland China. All patients received pre-treatment magnetic resonance imaging (MRI), and definitive radiotherapy with or without concurrent chemotherapy. We reassessed the features of the primary tumor (tumor size, primary location, and extent of invasion) and the involvement of lymph nodes at each level. According to the incidence of LNM, these levels were sequenced and sorted into drainage stations. Univariate and multivariate analyses were used to determine the risk factors for bilateral and regional lymph node metastasis.

Results

The cohort consisted of 195 piriform sinus cancers (PSC), 47 posterior wall cancers (PWC), and 2 post-cricoid cancers (PCC). A total of 176 patients (72.1%) presented with MRI-detectable LNMs. The overall LNM rates for level II-VI and retropharyngeal lymph nodes (RPLNs) were 59.0%, 52.9%, 14.3%, 1.6%, 2.9%, and 16.4%, respectively. Based on the prevalence of LNM at each level, we hypothesize that the lymphatic drainage of PSC was carried out in sequence along three stations: Level II and III (61.0% and 55.4%), Level IV and RPLN (15.9% and 11.3%), and Level V and VI (1.5% and 3.1%). For PWCs, lymphatic drainage is carried out at two stations: Level II, III, and RPLN (48.9%, 40.4%, and 34.0%) and Level IV-VI (6.4%, 0%, and 2.1%). According to univariate and multivariate analyses, posterior wall invasion was significantly correlated with bilateral LNM (P = 0.030, HR = 2.853 95%CI, 1.110-7.338) and RPLN metastasis (P = 0.017, HR = 2.880 95%CI, 1.209-6.862). However, pyriform sinus invasion was less likely to present with bilateral LNM (P = 0.027, HR = 0.311, 95%CI, 0.111-0.875) and RPLN metastasis (P = 0.028, HR = 0.346, 95%CI, 0.134-0.891).

Conclusions and Relevance

The primary tumor site and extent of invasion are related to the pattern of lymph node metastasis. That is, the metastasis would drainage station by station along different directions.

Prognostic Significance of Lactate Dehydrogenase in Patients Undergoing Surgical Resection for Laryngeal Squamous Cell Carcinoma

The aim is to estimate the prognostic value of lactate dehydrogenase (LDH) in patients undergoing surgical resection for laryngeal squamous cell carcinoma (LSCC). A total of 640 resected LSCC patients were included. Preoperative lactate dehydrogenase (LDH) was assessed. Kaplan-Meier survival analysis and Cox regression analysis were conducted for overall survival (OS) and recurrence-free survival (RFS). Kaplan-Meier analysis, univariate analysis and multivariate analysis demonstrated significant prognostic value for preoperative LDH. Although LDH was predictor of OS, it failed to be a predictor of RFS. The univariate HR and 95% CI of LDH were 0.484 and 0.357-0.658 (P < 0.0001). The multivariate analysis showed that LDH (HR = 0.518, 95% CI: 0.380-0.705, p < 0.0001) was related to OS. Elevated preoperative LDH >132 IU/L was significantly associated with better survival. Preoperative LDH might be an independent prognostic marker of OS in LSCC patients undergoing surgical resection.

High Iodine Nutrition May Be a Risk Factor for Cervical Lymph Node Metastasis in Papillary Thyroid Cancer Patients

PURPOSE

The aim of this study was to retrospectively identify the effect of iodine on the papillary thyroid cancer (PTC) process and investigate the risk clinicopathologic characteristics of cervical lymph node metastasis (CLNM) for achieving a better preventive strategy of PTC.

METHODS

Totally 187 patients with CLNM and 279 without CLNM (NCLNM) were enrolled, and their urinary iodine concentration (UIC) and serum iodine concentration (SIC) were measured. Logistic regressions were used to reveal the effects of iodine nutrition on the CLNM status of PTC.

RESULTS

The levels of thyroid-stimulating hormone (TSH) and thyroglobulin (TG) were higher in the CLNM group than in the NCLNM group. UIC and SIC were positively correlated, and both of them were correlated with TSH, free thyroxine, and TG. The proportions of UIC >300 μg/L and of SIC >90 μg/L were higher in the CLNM than in the NCLNM. Logistic analysis showed that SIC >90 μg/L was an independent predictor for CLNM in PTC. Additionally, age ≥45, female, TG, multifocality, and diameter of cancer invasion >1 cm also affected CLNM status in PTC, and their logistic regression model showed a certain diagnostic accuracy (area under the receiver-operating characteristic curve = 0.72).

CONCLUSIONS

Relatively high iodine nutrition seemed to be a significant risk factor for the occurrence of CLNM in PTC and may promote lymphatic metastasis in PTC.

Histone deacetylase 1 regulates the malignancy of oral cancer cells via miR-154-5p/PCNA axis

Histone deacetylases (HDACs) can regulate the progression of various cancers, while their roles in oral cancer cells are not well known. Our present study found that the HDAC1 was over expressed in oral squamous cell carcinoma (OSCC) cells and tissues. Targeted inhibition of HDAC1 via its specific inhibitor PCI24781 or siRNA can inhibit the proliferation of OSCC cells and increase their sensitivity to the chemo-sensitivity such as doxorubicin treatment. HDAC1 can regulate the expression of proliferating cell nuclear antigen (PCNA) via decreasing its mRNA stability. While over expression of PCNA can attenuate HDAC1 inhibition induced suppression of cell proliferation. We checked the expression of various miRNAs which can target the 3'UTR of PCNA. Results showed that HDAC1 can negative regulate the expression of miR-154-5p, inhibitor of miR-154-5p can attenuate PCI24781 treatment decreased PCNA expression and cell proliferation. Collectively, our present study suggested that HDAC1 can promote the growth and progression of OSCC via regulation of miR-154-5p/PCNA signals.

Retropharyngeal Lymph Node Metastasis Diagnosed by Magnetic Resonance Imaging in Hypopharyngeal Carcinoma: A Retrospective Analysis From Chinese Multi-Center Data

Background

To assess the prevalence, risk factors and prognostic significance of retropharyngeal lymph node (RPLN) metastasis diagnosed by magnetic resonance imaging (MRI) in patients with hypopharyngeal squamous cell carcinoma (HPSCC).

Methods

259 patients from three cancer institutions in China from Jan 2010 to Dec 2018 were analyzed, retrospectively. All the patients had been given pre-treatment magnetic resonance imaging (MRI) of head and neck and were then treated with definitive radiotherapy with or without chemotherapy. Pretreatment diagnostic MRIs were reviewed by a dedicated head and neck radiologist, for the presence or absence of radiographically positive RPLN, cervical LN and tumor invasion.Demographic variables were analysed by descriptive statistics using SPSS 20.0. Predictors of the presence of RPLN and its prognostic significance were examined.

Results

RPLN metastasis was discovered in 44 patients (17%). Logistic analysis showed that posterior pharyngeal wall (PPW) primary tumor; PPW invasion; N2-3; multiple cervical lymph node (LN) involvement (>2 LNs) were associated with RPLN metastasis, with metastasis rates 37%, 30%, 31% and 33% respectively. Patients with RPLN metastasis had a significantly reduced 5-year overall survival (OS) and disease-free survival (DFS) compared to the non-RPLN metastasis group (OS 28% vs. 48%, p=0.001; DFS 25% vs. 41%, p=0.040).

Conclusions

RPLN metastasis was not uncommon in HPSCC patients. Risk factors were: PPW primary tumor, PPW invasion and cervical LN status. RPLN metastasis is a poor prognosticator for survival.

Identification of Immune-Related LncRNA Pairs for Predicting Prognosis and Immunotherapeutic Response in Head and Neck Squamous Cell Carcinoma

Long noncoding RNAs (lncRNAs) have multiple functions with regard to the cancer immunity response and the tumor microenvironment. The prognosis of head and neck squamous cell carcinoma (HNSCC) is still poor currently, and it may be effective to predict the clinical outcome and immunotherapeutic response of HNSCC by immunogenic analysis. Therefore, by using univariate COX analysis and Lasso Cox regression, we identified a signature consisting of 21 immune-related lncRNA pairs (IRLPs) that predicted clinical outcome and Immunotherapeutic response in HNSCC. Specifically, it was associated with immune cell infiltration (i.e., T cells CD4 memory resting, CD8 T cells, macrophages M0, M2, and NK cells), and more importantly this signature was strongly related with immune checkpoint inhibitors (ICIs) [such as PDCD1 (r = -0.35, P < 0.001), CTLA4 (r = -0.26, P < 0.001), LAG3 (r = -0.22, P < 0.001) and HAVCR2 (r = -0.2, P < 0.001)] and immunotherapy-related biomarkers (MMR and HLA). The present study highlighted the value of the 21 IRLPs signature as a predictor of prognosis and immunotherapeutic response in HNSCC.

LncRNA LINC-PINT Inhibits Malignant Behaviors of Laryngeal Squamous Cell Carcinoma Cells via Inhibiting ZEB1

Objective: Laryngeal squamous cell carcinoma (LSCC) belongs to head and neck squamous cell carcinoma (HNSCC), with dismal prognosis. Here, this study aims to disclose the role of LINC-PINT in cancer development, which may contribute to improving the clinical outcomes of LSCC treatment.

Methods: LINC-PINT expression in LSCC tissues and in TU-177 and Hep-2 cells was quantified, and subsequently, the association between LINC-PINT and LSCC malignancies was analyzed. pcDNA3.1-LINC-PINT or pcDNA3.1-EZH2 was introduced into Hep-2 and TU-177 cells. qRT-PCR and Western blot analyses examined the levels of proteins related to the AKT/mTOR pathway and their phosphorylated proteins in Hep-2 and TU-177 cells. The viability as well as migration and invasion abilities of Hep-2 and TU-177 cells were determined. Also, the distribution of LINC-PINT in Hep-2 cells was investigated as well as the interplay between LINC-PINT and EZH2. The downstream genes that might interact with EZH2 were screened.

Results: LINC-PINT expression was inhibited in LSCC tissues and in Hep-2 and TU-177 cells, whose downregulation was associated with unsatisfactory prognosis. LINC-PINT overexpression suppressed the proliferative, migratory and invasive capacities of Hep-2 and TU-177 cells. LINC-PINT, mainly expressing in nuclei, could enrich EZH2 to silence ZEB1. In Hep-2 and TU-177 cells, the inhibition of LINC-PINT or overexpression of ZEB1 could enhance cell proliferation, migration and invasion. The phosphorylated levels of proteins related to the AKT/mTOR pathway were declined in cells with LINC-PINT overexpression, and the levels of these phosphorylated proteins were increased in cells with LINC-PINT inhibition.

Conclusion: LINC-PINT enriches EZH2 to silence ZEB1 and thus inhibits the proliferative, migratory, and invasive capacities of Hep-2 and TU-177 cells. In addition, LINC-PINT might exert its biological function through the AKT/mTOR pathway.

Phototherapy together with it triggered immunological response for Anti-HPV treatment of oropharyngeal cancer: Removing tumor and pathogenic virus simultaneously

Oropharyngeal squamous cell carcinoma (OPSCC) is one of most common cancers that often brings lots of inconvenience to the patient in swallowing and phonation even after the operation. Moreover, OPSCC is typically as nodal metastases and high recurrence rate due to the high-risk human papillomavirus (HPV) infection for 90% of patients. Obviously, completely curing OPSCC requires simultaneous removal of solid tumor and related pathogenic virus, which is very indispensable but never be realized by any kind of clinical therapy up to now. In this work, we selected the ZrC nanoparticles as difunctional photoactive substance for synchronous generation of hyperthermia and reactive oxygen species (ROS) under NIR excitation. The resultant synergistic photothermal and photodynamic treatment outcome contributed to an excellent anti-tumor effect. The phototherapy of this work was found not only to be able to damage cancer cells directly, but also could trigger the host immunity for further tumor removal and desirable HPV inactivation. An immunologic mechanism of this work was reasonable proposed by monitoring level of shock protein (HSP), calreticulin (CRT), T lymphocytes and dendritic cells (DCs) and immune check point of B7H3, B7H4 and PD-L1 post phototherapy. It was found that tumor-associated antigens of CRT ("eat-me" signal), HSPs and cell debris were released as cancer cell damage, and then the adaptive immune system and the congenital immunity were triggered to activate DCs maturity, antigen presentation to T cells, proliferation of CD4⁺ and CD8⁺ T cells, recruiting macrophages and NK cells and so forth immune responses. Being the first example of using phototherapy for virus-related cancer study, this work opens the door for photo-immunotherapy.

Prognostic value of platelet distribution width and mean platelet volume in patients with laryngeal cancer

Aims: To investigate the prognostic relevance of platelet volume indices for survival in laryngeal cancer. Patients & methods: The study included 640 patients with laryngeal cancer. We analyzed the optimal cutoff values through receiver operating characteristic analysis, then analyzed the univariate factor and multivariate variables. Kaplan-Meier curves and log-rank tests were conducted to compare the overall survival (OS) and recurrence-free survival rates between the groups. Results: In multivariate analysis, elevated platelet distribution width (PDW) and PDW/platelet count ratio were significantly correlated with poor prognosis for OS; however, elevated mean platelet volume (MPV) and MPV/platelet count ratio suggested a notable correlation with favorable prognosis for OS. Meanwhile, elevated PDW and decreased MPV were significantly correlated with poor prognosis for recurrence-free survival. Conclusions: Our findings indicate that elevated PDW and decreased MPV could serve as independent biomarkers for worse survival in laryngeal cancer.

The roles of extracellular vesicles in the development, microenvironment, anticancer drug resistance, and therapy of head and neck squamous cell carcinoma

Head and neck squamous cell carcinoma (HNSCC) is one of the main malignant tumours affecting human health, mainly due to delayed diagnosis and high invasiveness. Extracellular vehicles (EVs) are membranous vesicles released by cells into the extracellular matrix that carry important signalling molecules and stably and widely exist in various body fluids, such as plasma, saliva, cerebrospinal fluid, breast milk, urine, semen, lymphatic fluid, synovial fluid, amniotic fluid, and sputum. EVs transport almost all types of bioactive molecules (DNA, mRNAs, microRNAs (miRNAs), proteins, metabolites, and even pharmacological compounds). These "cargoes" can act on recipient cells, reshaping the surrounding microenvironment and altering distant targets, ultimately affecting their biological behaviour. The extensive exploration of EVs has deepened our comprehensive understanding of HNSCC biology. In this review, we not only summarized the effect of HNSCC-derived EVs on the tumour microenvironment but also described the role of microenvironment-derived EVs in HNSCC and discussed how the "mutual dialogue" between the tumour and microenvironment mediates the growth, metastasis, angiogenesis, immune escape, and drug resistance of tumours. Finally, the clinical application of EVS in HNSCC was assessed.

SAT0564 BONE TEXTURE ANALYSIS WITH DEEP LEARNING IN HAND RADIOGRAPHS FOR ASSESSING THE RISK OF RHEUMATOID ARTHRITIS

Background:

Conventional x-rays are essential to identify radiographic changes of rheumatoid arthritis (RA) in structure and bone texture. Limited evidence suggests that the bone texture analysis may quantify the radiographic changes in RA;1however, current techniques such as the fractal dimension characterize fixed texture features. Deep learning offers novel methods to ‘learn’ radiographic texture features relevant to RA.

Objectives:

To develop a deep learning model to assess the radiographic bone texture in the distal metacarpal bone relevant to RA.

Methods:

We collected 3,738 conventional hand radiographs from 2,128 individuals (RA, n = 908; non-RA, n = 1220). The second, third, and fourth metacarpal bone images were segmented using a curve Graph Convolutional Network (GCN), and the distal third was used as the input to train a texture model to classify RA. The texture model was based on the Deep Texture Encoding Network (Deep-TEN) architecture (figure 1),2which put an encoding layer on top of a pre-trained 18-layered residual network (ResNet18). The vectors produced by the model represent the orderless texture features that were used to generate a texture score for RA. Five texture models are trained using 5-fold cross-validation and are ensembled during inference by averaging the model outputs to produce the final score. We then validate the model using hand radiographs of 166 RA patients and 166 non-RA patients. Overall model performance was measured by area under the curve of the receiver operator curve (AUROC). Multivariate logistic regression was used to estimate the odds ratio (OR) and 95% confidence interval (CI) of RA.

Figure 1.

Schematic representation of deep learning models to extract and encode texture features for RA classification.

Results:

We included 140 women and 26 men with RA (mean age, 55.9±1.8 years) and 166 non-RA individuals (F: M, 140:26; mean age, 55.5 ± 1.8 years). The mean texture score was 0.49 (95% CI, 0.48–0.50) in RA patients, which is significantly higher than non-RA patients (0.42, 95% CI, 0.40–0.43; p<0.01). The AUROC of the model was 0.68. In the multivariate logistic regression model, a high texture score (>0.43) is associated with an OR (95% CI) of 3.42 (2.48–4.72) for RA, adjusted by age and sex.

Conclusion:

This study indicates that the texture model can delineate radiographic changes in texture relevant to RA and, coupled with automatic joint detection and segmentation, it has the potential to aid early RA diagnosis and monitor radiographic progression.

References:

[1]Zandieh S, Haller J, Bernt R, et al. Fractal analysis of subchondral bone changes of the hand in rheumatoid arthritis. Medicine (Baltimore) 2017;96(11):e6344.

[2]Zhang H, Xue J, Dana K. Deep TEN: Texture Encoding Network. The IEEE Conference on Computer Vision and Pattern Recognition (CVPR) 2017:708-17.

Disclosure of Interests:

None declared

OP0301 PREDICTION OF LOW BONE MINERAL DENSITY AND FRAX SCORE BY ASSESSING HIP BONE TEXTURE WITH DEEP LEARNING

Background:

Osteoporosis is a widespread health concern associated with an increased risk of fractures in individuals with low bone mineral density (BMD). Dual-energy x-ray absorptiometry (DXA) is the gold standard to measure BMD, but methods based on the assessment of plain films, such as the digital radiogrammetry,1are also available. We describe a novel approach based on the assessment of hip texture with deep learning to estimate BMD.

Objectives:

To compare the BMD estimated by assessing hip texture using a deep learning model and that measured by DXA.

Methods:

In this study, we identified 1,203 patients who underwent DXA of left hip and hip plain film within six months. The dataset was split into a training set with 1,024 patients and a testing set with 179 patients. Hip images were obtained and regions of interest (ROI) around left hips were segmented using a tool based on the curve Graph Convolutional Network. The ROIs are processed using a Deep Texture Encoding Network (Deep-TEN) model,2which comprises the first 3 blocks of Residual Network with 18 layers (ResNet-18) model followed by a dictionary encoding operator (Figure 1). The encoded features are processed using a fully connected layer to estimate BMD. Five-fold cross-validation was conducted. Pearson’s correlation coefficient was used to assess the correlation between predicted and reference BMD. We also test the performance of the model to identify osteoporosis (T-score ≤ -2.5)

Figure 1.

Schematic representation of deep learning models to extract and encode texture features for estimation of hip bone density.

Results:

We included 151 women and 18 men in the testing dataset (mean age, 66.1 ± 1.7 years). The mean predicted BMD was 0.724 g/cm2compared with the mean BMD measured by DXA of 0.725 g/cm2(p = 0.51). Pearson’s correlation coefficient between predicted and true BMD was 0.88. The performance of the model to detect osteoporosis/osteopenia was shown in Table 1. The positive predictive value was 87.46% for a T-score ≤ -1 and 83.3% for a T-score ≤ -2.5. Furthermore, the mean FRAX® 10-year major fracture risk did not differ significantly between scores based on predicted (6.86%) and measured BMD (7.67%, p=0.52). The 10-year probability of hip fracture was lower in the predicted score (1.79%) than the measured score (2.43%, p = 0.01).

Table 1.

Performance matrices of the deep texture model to detect osteoporosis/osteopenia

T-score ≤ -1T-score ≤ -2.5Sensitivity91.11%(95% CI, 83.23% to 96.08%)33.33%(95% CI, 17.29% to 52.81%)Specificity86.08%(95% CI, 76.45% to 92.84%)98.56%(95% CI, 94.90% to 99.83%)Positive predictive value88.17%(95% CI, 81.10% to 92.83%)83.33%(95% CI, 53.58% to 95.59%)Negative predictive value89.47%(95% CI, 81.35% to 94.31%)87.26%(95% CI, 84.16% to 89.83%)

Conclusion:

This study demonstrates the potential of the bone texture model to detect osteoporosis and to predict the FRAX score using plain hip radiographs.

References:

[1]Zandieh S, Haller J, Bernt R, et al. Fractal analysis of subchondral bone changes of the hand in rheumatoid arthritis. Medicine (Baltimore) 2017;96(11):e6344.

[2]Zhang H, Xue J, Dana K. Deep TEN: Texture Encoding Network. The IEEE Conference on Computer Vision and Pattern Recognition (CVPR) 2017:708-17.

Disclosure of Interests:

None declared

OP0062 PREDICTIVE VALUE OF BONE TEXTURE FEATURES EXTRACTED BY DEEP LEARNING MODELS FOR THE DETECTION OF OSTEOARTHRITIS: DATA FROM THE OSTEOARTHRITIS INITIATIVE

Background:

Osteoarthritis is a degenerative disorder characterized by radiographic features of asymmetric loss of joint space, subchondral sclerosis, and osteophyte formation. Conventional plain films are essential to detect structural changes in osteoarthritis. Recent evidence suggests that fractal- and entropy-based bone texture parameters may improve the prediction of radiographic osteoarthritis.1In contrast to the fixed texture features, deep learning models allow the comprehensive texture feature extraction and recognition relevant to osteoarthritis.

Objectives:

To assess the predictive value of deep learning-extracted bone texture features in the detection of radiographic osteoarthritis.

Methods:

We used data from the Osteoarthritis Initiative, which is a longitudinal study with 4,796 patients followed up and assessed for osteoarthritis. We used a training set of 25,978 images from 3,086 patients to develop the textual model. We use the BoneFinder software2to do the segmentation of distal femur and proximal tibia. We used the Deep Texture Encoding Network (Deep-TEN)3to encode the bone texture features into a vector, which is fed to a 5-way linear classifier for Kellgren and Lawrence grading for osteoarthritis classification. We also developed a Residual Network with 18 layers (ResNet18) for comparison since it deals with contours as well. Spearman’s correlation coefficient was used to assess the correlation between predicted and reference KL grades. We also test the performance of the model to identify osteoarthritis (KL grade≥2).

Results:

We obtained 6,490 knee radiographs from 446 female and 326 male patients who were not in the training sets to validate the performance of the models. The distribution of the KL grades in the training and testing sets were shown in Table 1. The Spearman’s correlation coefficient was 0.60 for the Deep-TEN and 0.67 for the ResNet18 model. Table 2 shows the performance of the models to detect osteoarthritis. The positive predictive value for Deep-TEN and ResNet18 model classification for OA was 81.37% and 87.46%, respectively.

Table 1

Distribution of KL grades in the training and testing sets.

KL grades01234TotalTraining set1089341.9%458218.7%611423.5%332012.8%7993.1%25,978Testing set247238.1%135320.8%169626.1%77511.9%1943.0%6,490Table 2

Performance matrices of the Deep-Ten and ResNet18 models to detect osteoarthritis

Deep-TENResNet18Sensitivity62.29%(95% CI, 60.42%–64.13%)59.14%(95% CI, 57.24%–61.01%)Specificity90.07%(95% CI, 89.07%–91.00%)94.09%(95% CI, 93.30%–94.82%)Positive predictive value81.37%(95% CI, 79.81%–82.84%)87.46%(95% CI, 85.96%–88.82%)Negative predictive value77.42%(95% CI, 77.64%–79.65%)76.77%(95% CI, 75.93%–77.59%)

Conclusion:

This study demonstrates that the bone texture model performs reasonably well to detect radiographic osteoarthritis with a similar performance to the bone contour model.

References:

[1]Bertalan Z, Ljuhar R, Norman B, et al. Combining fractal- and entropy-based bone texture analysis for the prediction of osteoarthritis: data from the multicenter osteoarthritis study (MOST). Osteoarthritis Cartilage 2018;26:S49.

[2]Lindner C, Wang CW, Huang CT, et al. Fully Automatic System for Accurate Localisation and Analysis of Cephalometric Landmarks in Lateral Cephalograms. Sci Rep 2016;6:33581.

[3]Zhang H, Xue J, Dana K. Deep TEN: Texture Encoding Network. The IEEE Conference on Computer Vision and Pattern Recognition (CVPR) 2017:708-17.

Disclosure of Interests:

None declared

BCL2 and hsa-miR-181a-5p are potential biomarkers associated with papillary thyroid cancer based on bioinformatics analysis

Background

The morbidity of thyroid carcinoma has been rising worldwide and increasing faster than any other cancer type. The most common subtype with the best prognosis is papillary thyroid cancer (PTC); however, the exact molecular pathogenesis of PTC is still not completely understood.

Methods

In the current study, 3 gene expression datasets (GSE3678, GSE3467, and GSE33630) and 2 miRNA expression datasets (GSE113629 and GSE73182) of PTC were selected from the Gene Expression Omnibus (GEO) database and were further used to identify differentially expressed genes (DEGs) and deregulated miRNAs between normal thyroid tissue samples and PTC samples. Then, Gene Ontology (GO) and pathway enrichment analyses were conducted, and a protein-protein interaction (PPI) network was constructed to explore the potential mechanism of PTC carcinogenesis. The hub gene detection was performed using the CentiScaPe v2.0 plugin, and significant modules were discovered using the MCODE plugin for Cytoscape. In addition, a miRNA-gene regulatory network in PTC was constructed using common deregulated miRNAs and DEGs.

Results

A total of 263 common DEGs and 12 common deregulated miRNAs were identified. Then, 6 significant KEGG pathways (P < 0.05) and 82 significant GO terms were found to be enriched, indicating that PTC was closely related to amino acid metabolism, development, immune system, and endocrine system. In addition, by constructing a PPI network and miRNA-gene regulatory network, we found that hsa-miR-181a-5p regulated the most DEGs, while BCL2 was targeted by the most miRNAs.

Conclusions

The results of this study suggested that hsa-miR-181a-5p and BCL2 and their regulatory networks may play important roles in the pathogenesis of PTC.

HOXA11-AS promotes the progression of oral squamous cell carcinoma by targeting the miR-518a-3p/PDK1 axis

Background

Long non-coding RNAs (lncRNAs) are promising therapeutic molecules of cancer. Here we aim to study the therapeutic effect and mechanism of a lncRNA, HOXA11-AS, in oral squamous cell carcinoma (OSCC).

Methods

OSCC tissues and adjacent matched paraneoplastic normal tissues used in this study were collected from 42 OSCC patients. The significant downregulation or upregulation of HOXA11-AS expression in OSCC cells was confirmed by quantitative real-time PCR (qRT-PCR). Bioinformatics analysis of StarBase were performed to investigate the potential microRNAs mediated by HOXA11-AS. HOXA11-AS-transfected cells or control cells were subcutaneously injected into nude mice to further determine the effects of HOXA11-AS on OSCC progression in vivo.

Results

qRT-PCR analysis indicated that HOXA11-AS expression was significantly upregulated in OSCC tissues. Functional studies revealed that HOXA11-AS significantly promotes cell proliferation, reduces the percentage of G0/G1 phase cells and enhances the cell invasion in OSCC. Bioinformatics analysis suggested that a microRNA (miRNA), miR-518a-3p, is as a target of HOXA11-AS. Alteration of miR-518a-3p levels by HOXA11-AS transduced to changes in PDK1 expression. In a mouse model of OSCC, HOXA11-AS overexpression promoted tumor growth, concomitant with reduced miR-518a-3p expression and increased PDK1 expression.

Conclusion

Taken together, our study demonstrates that HOXA11-AS/miR-518a-3p/PDK1 axis is an important regulator of OSCC progression and may serve as a potential therapeutic target in OSCC. HARMU20150128, registered at Jan, 28 2018.

Long non-coding RNA AFAP1-AS1/miR-320a/RBPJ axis regulates laryngeal carcinoma cell stemness and chemoresistance

AFAP1-AS1 is a long non-coding RNA that is associated with tumorigenesis and poor prognosis in a variety of cancers. We have been suggested that AFAP1-AS1 increases tumorigenesis in laryngeal carcinoma specifically by enhancing stemness and chemoresistance. We assessed AFAP1-AS1 expression in human laryngeal specimens, paired adjacent normal tissues and human HEp-2 cells. Indeed, we found not only that AFAP1-AS1 was up-regulated in laryngeal carcinoma specimens and cells, but also that stemness-associated genes were overexpressed. Silencing of AFAP1-AS1 promoted HEp-2 cell chemoresistance under cisplatin treatment. Expression of AFAP1-AS1 was increased in drug-resistant Hep-2 cells. We then probed the mechanism of AFAP1-AS1 activity and determined that miR-320a was a potential molecular target of AFAP1-AS1. Luciferase reporter and qRT-PCR assays of AFAP1-AS1 and miR-320a levels in human specimens and cell cultures indicated that AFAP1-AS1 negatively regulates miR-320a. To discover the molecular mechanism of miR-320a, we again used the DIANA Tools algorithm to predict its genetic target, RBPJ. After cloning the 3'-untranslated regions (3'-UTR) of RBPJ into a luciferase reporter, we determined that miR-320a did in fact reduce RBPJ mRNA and protein levels. Ultimately, we determined that AFAP1-AS1 increases RBPJ expression by negatively regulating miR-320a and RBPJ overexpression rescues stemness and chemoresistance inhibited by AFAP1-AS1 silencing. Taken together, these results suggest that AFAP1-AS1 can serve as a prognostic biomarker in laryngeal carcinoma and that miR-320a has the potential to improve standard therapeutic approaches to the disease, especially for cases in which cancer cell stemness and drug resistance present significant barriers to effective treatment.

MicroRNA-650 targets inhibitor of growth 4 to promote colorectal cancer progression via mitogen activated protein kinase signaling

Colorectal cancer (CRC) is the third most common malignant disease globally and causes numerous cancer-associated mortalities; however, the underlying molecular mechanisms remain unresolved. MicroRNAs (miRs) are endogenous noncoding RNAs that regulate post-transcriptional gene silencing by annealing to partially complementary sequences in the 3′-untranslated regions of target mRNAs. In the present study, expression of the tumor suppressor gene inhibitor of growth protein 4 (ING4) in cell lines was investigated using reverse transcription-quantitative polymerase chain reaction and western blotting. miR-650 overexpression promoted CRC cell proliferation and migration by targeting ING4 when the cells were transfected with the miR-650 mimics. Additionally, overexpression of miR-650 increased the epithelial-mesenchymal transition and activation of the Ras homolog gene family member A/Ras-related C3 botulinum toxin GTPase. Extracellular signal-regulated kinases and p38 mitogen-activated protein kinase signaling were markedly activated when miR-650 was increased in CRC cells. Combined, the results indicate the mechanism underlying the miR-650 promotion of CRC progression, and provide promising potential biomarkers for the prognosis and treatment of CRC.

miR-217 inhibits laryngeal cancer metastasis by repressing AEG-1 and PD-L1 expression

High incidences of laryngeal cancer have been reported recently. Increasing our understanding of the molecular mechanisms underlying this malignancy could reveal more effective approaches to treating laryngeal cancer patients and so improve their prognoses. In this study, we explored the biological effects of miR-217 on laryngeal cancer. miR-217 potently inhibited multiple metastatic traits, including cell migration, invasion, proliferation, apoptosis, and EMT, as well as angiogensis. These effects were achieved through downregulation of the miR-217 target gene, AEG-1 and PD-L1. Clinical expression and animal model studies further confirmed our results. These findings provide new insight into the physiological effects of miR-217 in laryngeal cancer and its potential therapeutic use.

Scatter to volume registration for model-free respiratory motion estimation from dynamic MRIs

Respiratory motion is one major complicating factor in many image acquisition applications and image-guided interventions. Existing respiratory motion estimation and compensation methods typically rely on breathing motion models learned from certain training data, and therefore may not be able to effectively handle intra-subject and/or inter-subject variations of respiratory motion. In this paper, we propose a respiratory motion compensation framework that directly recovers motion fields from sparsely spaced and efficiently acquired dynamic 2-D MRIs without using a learned respiratory motion model. We present a scatter-to-volume deformable registration algorithm to register dynamic 2-D MRIs with a static 3-D MRI to recover dense deformation fields. Practical considerations and approximations are provided to solve the scatter-to-volume registration problem efficiently. The performance of the proposed method was investigated on both synthetic and real MRI datasets, and the results showed significant improvements over the state-of-art respiratory motion modeling methods. We also demonstrated a potential application of the proposed method on MRI-based motion corrected PET imaging using hybrid PET/MRI.

Real-time 6DoF pose recovery from X-ray images using library-based DRR and hybrid optimization

PURPOSE

Real-time 6 degrees of freedom (6DoF) pose recovery and tracking from X-ray images is a key enabling technology for many interventional imaging applications. However, real-time 2D/3D registration is a very challenging problem because of the heavy computation in iterative digitally reconstructed radiograph (DRR) generation. In this paper, we propose a real-time 2D/3D registration framework using library-based DRRs to achieve high computational efficiency.

METHOD

The proposed method pre-computes a library of canonical DRRs and reconstructs library-based DRRs (libDRRs) during registration without online rendering. The transformation parameters are decoupled to 2 geometry-relevant and 4 geometry-irrelevant ones so that canonical DRRs only need to cover the variation of 2 geometry-relevant parameters, making it practical to be pre-computed and stored. The 2D/3D registration using libDRRs is then solved as a hybrid optimization problem, i.e., continuous in geometry-irrelevant parameters while discrete in geometry-relevant parameters.

RESULTS

On 5 fluoroscopic sequences with 246 frames acquired during animal studies with a transesophageal echocardiography (TEE) probe in the field of view, 6DoF tracking of the TEE probe using the proposed method achieved a mean target registration error in the projection direction (mTREproj) of 0.81 mm, a success rate of 100 % (defined as mTREproj [Formula: see text]2.5 mm), and a registration frame rate of 23.1 fps on a pure CPU-based implementation executed in a single thread.

CONCLUSION

Using libDRRs with a hybrid optimization can significantly improve the computational efficiency (up to tenfold) for 6DoF pose recovery and tracking with little degradation in robustness and accuracy, compared to conventional intensity-based 2D/3D registration using ray casting DRRs with a continuous optimization.

Extraordinary high ductility/strength of the interface designed bulk W-ZrC alloy plate at relatively low temperature

The refractory tungsten alloys with high ductility/strength/plasticity are highly desirable for a wide range of critical applications. Here we report an interface design strategy that achieves 8.5 mm thick W-0.5 wt. %ZrC alloy plates with a flexural strength of 2.5 GPa and a strain of 3% at room temperature (RT) and ductile-to-brittle transition temperature of about 100 °C. The tensile strength is about 991 MPa at RT and 582 MPa at 500 °C, as well as total elongation is about 1.1% at RT and as large as 41% at 500 °C, respectively. In addition, the W-ZrC alloy plate can sustain 3.3 MJ/m² thermal load without any cracks. This processing route offers the special coherent interfaces of grain/phase boundaries (GB/PBs) and the diminishing O impurity at GBs, which significantly strengthens GB/PBs and thereby enhances the ductility/strength/plasticity of W alloy. The design thought can be used in the future to prepare new alloys with higher ductility/strength.

Effect of EphA7 Silencing on Proliferation, Invasion and Apoptosis in Human Laryngeal Cancer Cell Lines Hep-2 and AMC-HN-8

AIMS

This study aimed to investigate the expression of EphA7 in human laryngeal squamous cell carcinoma (LSCC) tissues and disclose the potential roles and molecular mechanisms of EphA7 in LSCC.

METHODS

In the present study, we examined EphA7 expression and its function and mechanism in LSCC. EphA7 expression levels were investigated by quantitative real-time PCR (qRT-PCR), western blotting, and immunohistochemistry in a panel of 35 LSCC patient cases. To investigate the potential mechanism of EphA7 in human laryngeal cancer, we employed EphA7 siRNA to knockdown EphA7 expression in LSCC cell line Hep-2 and AMC-HN-8. Subsequently, MTT, TUNEL, qRT-PCR, and western blotting were performed to disclose the roles of EphA7 on proliferation, invasion and migration, and apoptosis in LSCC cell line Hep-2 and AMC-HN-8.

RESULTS

Depletion of EphA7 remarkably inhibited the proliferation and invasion of Hep-2 and AMC-HN-8 cells in comparison to control and EphA7 siRNA negative control (NC)-transfected cells. TUNEL staining assay demonstrated that, compared with the control group, the rate of apoptosis in the EphA7 siRNA group was significantly increased. In addition, knockdown of EphA7 in Hep-2 or AMC-HN-8 cells markedly decreased the expression of EphA7 and PTEN, which could contribute to apoptosis. However, the bpV(phen), a PTEN inhibitor, could attenuate anti-proliferation and pro-apoptotic effects of EphA7 siRNA in Hep-2 and AMC-HN-8 cells.

CONCLUSION

Up-regulation of EphA7 was observed in human LSCC samples and down-regulation of EphA7 effectively suppressed laryngeal carcinoma cell growth and promoted its apoptosis. Thus, EphA7 has a critical role in modulating cell growth and apoptosis, which serves as a potential therapeutic target in human LSCC.

INHIBITORY EFFECT OF TETRAMETHYLPYRAZINE ON HEPATOCELLULAR CARCINOMA: POSSIBLE ROLE OF APOPTOSIS AND CELL CYCLE ARREST

Hepatocellular carcinoma (HCC) is the fifth most common cancer. An important approach to control HCC is chemoprevention. This study aims at investigating the antitumor effect of Tetramethylpyrazine (TMP). Rats were injected with N-Nitrosodiethylamine (DEN) to establish HCC. Tumor development was observed. Liver function was evaluated. Apoptosis and cell cycle arrest-related makers and signaling cascades were determined by Western blot, RT-PCR and flow cytometric analysis. The administration of TMP could significantly inhibit tumor development in DEN-induced HCC rats, shown by reduced incidence of tumor, decreased number of tumor nodules and reduced maximal size of tumor. DEN-induced increase of aspartate aminotransferase, alanine aminotransferase, lactate dehydrogenase and alkaline phosphatase activities were significantly inhibited by TMP. TMP exhibited inhibitory effect on HCC through induction of apoptosis and cell cycle arrest in rats. TMP induced apoptosis through increasing Bax, decreasing Bcl-2, increasing the release of cytochrome c, and activating caspase, which consisted of the mitochondrial apoptotic pathway. TMP induced G2/M cell cycle arrest through down-regulation of cyclin B1/cdc2. In addition, inhibition of Akt and ERK signaling and the antioxidant activities of TMP may also contribute to its antitumor effect. These data provide new insight into the mechanisms underlying the antitumor effect of TMP.

Predictive factors for different subgroups of central lymph node metastasis in unilateral papillary thyroid carcinoma

AIMS

We aimed to investigate the incidence rates and risk factors for different subgroups of central neck lymph node (LN) metastasis (prelaryngeal, ipsilateral paratracheal, pretracheal, and contralateral paratracheal) in unilateral papillary thyroid carcinoma (PTC) patients with clinically negative neck nodes (cN0).

METHODS

We evaluated 184 patients from 2007 to 2009. The relationships between different subgroups of LN metastasis and clinical pathological factors were analyzed.

RESULTS

The incidence rates of different central LN metastases were diverse. Multivariate analysis indicated that lymphovascular invasion, perithyroidal invasion, and tumor size were risk factors for ipsilateral paratracheal central LN metastasis; tumor size was an independent risk factor for pretracheal central LN metastasis, and pretracheal or/and ipsilateral paratracheal central LN metastasis were risk factors for contralateral paratracheal central LN metastasis.

CONCLUSION

The extent of elective central LN dissection (CLND) should be decided based on different clinical pathological factors in cN0 PTC patients. Moreover, elective prelaryngeal CLND may be unnecessary.