Nodule Status Research Articles

PAR1 Is a Candidate Target for the Treatment of Peritoneal Dissemination in Gastric Cancer.

Peritoneal dissemination (PD) is a frequent cause of death in gastric cancer (GC), and there is evidence of an association between protease-activated receptor-1 (PAR1) and the development of PD. This study hypothesized that PD in GC might be influenced by PAR1. The cytotoxic effect of paclitaxel (PTX) on PAR1-transfected MKN45 (MKN45/PAR1) cells was analyzed using the MTT assay, and IC50 values were determined. In female athymic nude mice, MKN45/PAR1 cells were suspended in 0.05 ml phosphate-buffered saline (PBS) medium and inoculated into the stomach mid-wall. In each group, intraperitoneal injections of PBS, PTX, SCH79797 (PAR1-antagonist), or PTX plus SCH79797 were administered on days 8, 15, and 22 following tumor inoculation. At 56 days after tumor inoculation, mice were examined for both abdominal tumor nodule status and size and weight of the tumors. The IC50 of PTX for MKN45/PAR1 cells was 0.0697 μM and that of SCH79797 was 0.0145 μM. Mean survival of the MKN45/PAR1 mice in the PBS group was 28.75 days, whereas survival times for the mice treated with SCH79797, PTX, or a combination of PTX and SCH79797 were 31.2, 49.2, and 48.5 days, respectively. Tumor weight was smaller in the group receiving PTX and SCH79797 intraperitoneally compared with that in the PBS group (1,086±127.2 mg vs. 33.2±19.9 mg; p<0.001). The PAR1 antagonist was found to inhibit PD in a PAR1-expressing GC cell line. PAR1 may serve as a promising therapeutic target for managing PD in gastric cancer, as it plays a crucial role in its progression.

Predictive value of IGF-1/IGFBP-3 ratio for thyroid nodules in type 2 diabetic mellitus.

To explore the predictive value of the IGF-1/IGFBP-3 ratio for the presence of thyroid nodules in patients with type 2 diabetes mellitus (T2DM). This observational study prospectively enrolled patients with T2DM at the Second Hospital of Jilin University between May 2021 and January 2022. Thyroid nodule (TN) status was determined by ultrasonography. Receiver operating characteristic (ROC) curve analysis was performed to assess the predictive value of the serum IGF-1/IGFBP-3 molar ratio for TNs. Multivariable logistic regression analysis was conducted to identify risk factors for thyroid nodules in patients with T2DM. A total of 122 patients (mean age ± standard deviation: 52.57 ± 11.71 years; 74 males) were enrolled. 37.7% (n=46) of patients did not have TNs, while 62.3% (n=76) had TNs. The duration of diabetes, age, and HDL-C level were significantly higher in the T2DM group with TNs compared to the group without TNs (all P < 0.05). The area under the ROC curve (AUC) for the combination of IGF-1, IGFBP-3, and the serum IGF-1/IGFBP-3 molar ratio in predicting TNs in T2DM patients was 0.619 (P < 0.001). Additionally, multivariable logistic regression analysis revealed that the duration of diabetes, age, fasting plasma glucose (FPG), fasting insulin (FINS), thyroid-stimulating hormone (TSH), IGF-1, and IGFBP-3 levels were independent risk factors for thyroid nodules, while the serum IGF-1/IGFBP-3 molar ratio level was an independent protective factor for thyroid nodules in patients with T2DM (all P < 0.05). The combination of IGF-1, IGFBP-3, and the serum IGF-1/IGFBP-3 molar ratio may have a better predictive value for TNs in T2DM patients than using any single marker alone. The duration of diabetes, age, FPG, FINS, TSH, IGF-1, IGFBP-3, and the serum IGF-1/IGFBP-3 molar ratio levels were independently associated with thyroid nodules in patients with T2DM.

Deep Learning Radiomics Features of Mediastinal Fat and Pulmonary Nodules on Lung CT Images Distinguish Benignancy and Malignancy.

This study investigated the relationship between mediastinal fat and pulmonary nodule status, aiming to develop a deep learning-based radiomics model for diagnosing benign and malignant pulmonary nodules. We proposed a combined model using CT images of both pulmonary nodules and the fat around the chest (mediastinal fat). Patients from three centers were divided into training, validation, internal testing, and external testing sets. Quantitative radiomics and deep learning features from CT images served as predictive factors. A logistic regression model was used to combine data from both pulmonary nodules and mediastinal adipose regions, and personalized nomograms were created to evaluate the predictive performance. The model incorporating mediastinal fat outperformed the nodule-only model, with C-indexes of 0.917 (training), 0.903 (internal testing), 0.942 (external testing set 1), and 0.880 (external testing set 2). The inclusion of mediastinal fat significantly improved predictive performance (NRI = 0.243, p < 0.05). A decision curve analysis indicated that incorporating mediastinal fat features provided greater patient benefits. Mediastinal fat offered complementary information for distinguishing benign from malignant nodules, enhancing the diagnostic capability of this deep learning-based radiomics model. This model demonstrated strong diagnostic ability for benign and malignant pulmonary nodules, providing a more accurate and beneficial approach for patient care.

SCCA and CYFRA 21-1 Reference Intervals for Apparently Healthy Chinese Adults: a Multicenter Cross-Sectional Study.

This study aimed to establish reference intervals for two biomarkers actively utilized in routine annual medical check-ups in China: squamous cell carcinoma antigen (SCCA) and cytokeratin 19 fragment (CYRFA 21-1), and to understand the influence of age, gender, and benign nodule(s) on their levels. This prospective multicenter cross-sectional study continuously enrolled apparently healthy adults attending annual medical check-ups at three sites in 2019. Serum SCCA and CYFRA 21-1 levels were measured using electrochemiluminescence immunoassays. Age- and gender-specific reference intervals for the two biomarkers were established by using the 0 - 95th percentiles with 90% confidence intervals (CIs). The 97.5th percentiles were also provided. A total of 1,017 subjects were enrolled in this study. Both biomarkers were significantly lower in females, and age was negatively associated with SCCA while positively associated with CYFRA 21-1 (all p < 0.0001). No statistically significant differences were determined between subgroups without/with benign nodule(s) despite nodule(s) status (all p > 0.05). The overall reference interval for SCCA is 0 - 2.64 ng/mL and 0 - 4.39 ng/mL for CYFRA 21-1. The age-specific reference intervals for SCCA are 0 - 2.76 ng/mL (18 - 49 years) and 0 - 2.22 ng/mL (≥ 50 years), and for CYFRA 21-1, they are 0 - 3.86 ng/mL (18 - 49 years) and 0 - 4.89 ng/mL (≥ 50 years). The gender-specific reference intervals for SCCA are 0 - 2.83 ng/mL (male) and 0 - 2.49 ng/mL (female), and for CYFRA 21-1, they are 0 - 4.34 ng/mL (male) and 0 - 4.45 ng/mL (female). The reference intervals for SCCA and CYFRA 21-1 established in this study could be utilized in annual medical check-ups and contribute to the screening of lung cancer in China.

Development and validation of a risk model with variables related to non-small cell lung cancer in patients with pulmonary nodules: a retrospective study

BackgroundLung cancer is a major global threat to public health for which a novel predictive nomogram is urgently needed. Non-small cell lung cancer (NSCLC) which accounts for the main port of lung cancer cases is attracting more and more people’s attention.Patients and methodsHere, we designed a novel predictive nomogram using a design dataset consisting of 515 pulmonary nodules, with external validation being performed using a separate dataset consisting of 140 nodules and a separate dataset consisting of 237 nodules. The selection of significant variables for inclusion in this model was achieved using a least absolute shrinkage and selection operator (LASSO) logistic regression model, after which a corresponding nomogram was developed. C-index values, calibration plots, and decision curve analyses were used to gauge the discrimination, calibration, and clinical utility, respectively, of this predictive model. Validation was then performed with the internal bootstrapping validation and external cohorts.ResultsA predictive nomogram was successfully constructed incorporating hypertension status, plasma fibrinogen levels, blood urea nitrogen (BUN), density, ground-glass opacity (GGO), and pulmonary nodule size as significant variables associated with nodule status. This model exhibited good discriminative ability, with a C-index value of 0.765 (95% CI: 0.722-0.808), and was well-calibrated. In validation analyses, this model yielded C-index values of 0.892 (95% CI: 0.844-0.940) for external cohort and 0.853 (95% CI: 0.807-0.899) for external cohort 2. In the internal bootstrapping validation, C-index value could still reach 0.753. Decision curve analyses supported the clinical value of this predictive nomogram when used at a NSCLC possibility threshold of 18%.ConclusionThe nomogram constructed in this study, which incorporates hypertension status, plasma fibrinogen levels, BUN, density, GGO status, and pulmonary nodule size, was able to reliably predict NSCLC risk in this Chinese cohort of patients presenting with pulmonary nodules.

Rate of benign nodule resection in a lung cancer screening program

PurposeScreening with low dose computed tomography (CT) can reduce lung cancer related death at the expense of unavoidable false positive results. The purpose of this study is to measure the rate of surgery for benign nodules, and evaluate characteristics of those nodules. Materials and methodsIn this study, we evaluated patients in the Lung Cancer Screening (LCS) program across a large tertiary healthcare network from 5/2015 through 10/2021 who underwent surgical resection for a lung nodule. We reviewed the pathology reports and subsequent follow-up to establish whether the nodule was benign or malignant. Imaging characteristics of the nodules were evaluated by a radiology fellow, and we recorded Lung-RADS category, nodule status (baseline, stable, new, growing), FDG uptake on PET/CT, and calculated the risk from the Brock model. ResultsDuring this time period, a total of 21,366 LCS CT was performed in 9050 patients, and 260 patients underwent a following surgical resection. Review of the pathology results revealed: 220 lung cancer (85%), 2 other malignancies (1%), and 38 benign findings (15%). Pathology of the benign nodules was as follows: 12 with scarring/fibrosis, 5 with benign neoplasms, 14 with infection/inflammation, and 7 with other diagnoses. Lung-RADS category was as follows: 4 (11%) Lung-RADS 2, 2 (5%) Lung-Rad 3, 11 (29%) Lung-RADS 4A, 13 (34%) Lung-RADS 4B, and 8 (21%) Lung-RADS 4X. The size of the nodules ranged from 4 to 41 mm with a median of 13 mm. 2 (5%) were ground glass, 10 (26%) were part-solid, and 26 (68%) were solid. FDG-PET/CT was performed in 19 out of 38 cases, of which: 2 (11%) had no uptake, 10 (53%) had mild uptake, 3 (16%) had moderate uptake, and 4 (21%) had intense uptake. Risk assessment by Brock calculator revealed that 9 (24) had <5% (very low) risk; 27 (71%) had 5–65% (low-intermediate) risk, and 2 (5%) had >65% (high) risk. ConclusionSurgical resection of benign nodules is unavoidable despite application of Lung-RADS guidelines in a modern screening program, with approximately 15% of surgeries being done for benign lesions.

High specificity lung cancer test to rule out cancer in non-malignant lung nodules found at LDCT.

e20533 Background: Lung Cancer (LC) is the leading cause of cancer death worldwide and smoking is the leading risk factor. Only 15% of patients with LC are still alive 5 years after diagnosis due to advanced diseases stage at diagnosis. Low-Dose Computed Tomography (LDCT) is the widely accepted standard for screening of individuals at high risk of lung cancer. However, LDCT has several limitations including the high prevalence of non-malignant pulmonary nodules detected leading to overdiagnosis, the potential harms of cumulative radiation dose and poor adherence to recommended follow-up. Therefore, novel blood-based tests could offer a simple follow confirmation approach and this test is designed to find those patients who DO NOT have cancer. Methods: We measured levels of nucleosomes, CEA and CYFRA21-1in a cohort of 912 subjects and report data relating to 184 smoker subjects referred for CT scan at National Taiwan University Hospital. The smoker patients were later confirmed to have either a LC (n = 129, including 59 patients at early stage (stage 0-I), 15 at stage II, 47 at late stage (III and IV) and 8 with unknown stage), or non-malignant nodules (n = 41), or control with no-nodules (n = 14). Whole blood was collected in EDTA plasma tubes for analysis by six different Nu.Q chemiluminescent magnetic microparticle immunoassays (Belgian Volition, Belgium) targeting H3.1-nucleosomes or different histone modifications (H3K9Me3-, H3K27Me3-, H3K36Me3-, H3K9Ac-, H3K14Ac-nucleosomes). CEA was analyzed on the Abbott ARCHITECT analyzer. CYFRA21-1 was analyzed on the Roche Cobas E411 analyzer. We evaluated each biomarker levels individually and in a combinatorial approach by logistic regression for their performance in discriminating subject with a LC vs non-malignant nodules. Results: Among the eight individual markers evaluated, the best area under the curve (AUC) in discriminating LC vs non-malignant nodule were observed for CEA, H3K9Ac-nucleosomes and CYFRA21-1 with an AUC of 0.68, 0.69 and 0.74, respectively and a specificity at 95% sensitivity of 9.5%, 7.3% and 21.4%, respectively. A logistic regression approach defined H3K9Ac-nucleosomes, CEA and CYFRA21-1 as the best panel of biomarkers tested to improve the discrimination between LC and non-malignant nodules relatives to the markers alone, achieving a specificity of 34.1% at 95% sensitivity and an AUC of 0.80. 55 out of the 59 stage 0-I, 25/26 stage III and 20/21 stage IV LC were detected by this combination of markers while 34.1 % of the patients with benign nodules are found negative and not sent to unnecessary biopsy to ascertain the nodule status. Conclusions: Results of our proof-of-concept study indicate that a blood test combining H3K9Ac-nucleosome levels with CEA and CYFRA21-1 levels could help to rule-out patients with a non-malignant nodule offering a non-invasive tool as an aid to the decision-making process of the malignancy status of nodules detected by LDCT.

Development of a Structured Query Language and Natural Language Processing Algorithm to Identify Lung Nodules in a Cancer Centre.

Importance: The stratification of indeterminate lung nodules is a growing problem, but the burden of lung nodules on healthcare services is not well-described. Manual service evaluation and research cohort curation can be time-consuming and potentially improved by automation.Objective: To automate lung nodule identification in a tertiary cancer centre.Methods: This retrospective cohort study used Electronic Healthcare Records to identify CT reports generated between 31st October 2011 and 24th July 2020. A structured query language/natural language processing tool was developed to classify reports according to lung nodule status. Performance was externally validated. Sentences were used to train machine-learning classifiers to predict concerning nodule features in 2,000 patients.Results: 14,586 patients with lung nodules were identified. The cancer types most commonly associated with lung nodules were lung (39%), neuro-endocrine (38%), skin (35%), colorectal (33%) and sarcoma (33%). Lung nodule patients had a greater proportion of metastatic diagnoses (45 vs. 23%, p < 0.001), a higher mean post-baseline scan number (6.56 vs. 1.93, p < 0.001), and a shorter mean scan interval (4.1 vs. 5.9 months, p < 0.001) than those without nodules. Inter-observer agreement for sentence classification was 0.94 internally and 0.98 externally. Sensitivity and specificity for nodule identification were 93 and 99% internally, and 100 and 100% at external validation, respectively. A linear-support vector machine model predicted concerning sentence features with 94% accuracy.Conclusion: We have developed and validated an accurate tool for automated lung nodule identification that is valuable for service evaluation and research data acquisition.

Isfahan Thyroid Cohort Study (ITCS).

The Isfahan Thyroid Cohort Study (ITCS) is one of the few population-based epidemiological studies in Iran that investigates the prevalence and incidence of thyroid disorders including hypothyroidism, hyperthyroidism, goiter, nodule, and iodine status. This cohort is located in Isfahan, Iran. The first phase was initiated in 2006 with 2523 participants (1275 males, 1248 females). The participants were selected using multi-stage cluster sampling from the general residents of Isfahan, Iran. The study had two phases (2006 and 2011) and its third stage is planned for 2020-2021. The prevalence of thyroid function states was euthyroid (89.3%, 95% CI: 88%-90%), overt hypothyroidism (2.8%, 95% CI: 2%‒3%), subclinical hypothyroidism (5.8%, 95% CI: 4%-6%), overt hyperthyroidism (0.8%, 95% CI: 0.4%‒1%), and subclinical hyperthyroidism (0.99%, 95% CI: 0.6%-1%). Hypothyroidism and hyperthyroidism were significantly associated with goiter. The incidence of thyroid dysfunction was reported as follows: overt hypothyroidism (2.7, 95% CI: 1.6-3.7), subclinical hypothyroidism (20.6, 95% CI: 18-23), overt hyperthyroidism (1.9, 95% CI: 1-2.7) and subclinical hyperthyroidism (2.7, 95% CI: 1.6-3.7) per 1000 (person-year). We assessed the prevalence and incidence of thyroid disorders in Isfahan in the first and second phase, respectively. We are conducting the third phase of the ITCS in order to study the associations between thyroid peroxidase antibody (TPOAb) level and environmental factors such as infection.

Selenium, Zinc, and Copper Status in Euthyroid Nodular Goiter: A Cross-Sectional Study.

Background:It is known that some elements are needed for normal thyroid gland functions. Iodine and selenium are the most well-known trace elements necessary for thyroid metabolism. Selenium is involved in the formation of thyroid hormones and the structure of the deiodinases associated with the development of the thyroid gland. While the role of zinc in thyroid metabolism is at the T3 receptor level, the role of copper is yet not clear.Objective:To compare the levels of serum trace elements such as selenium, zinc, and copper between the patients with euthyroid nodular goiter and healthy participants.Methods:This cross-sectional study included 98 patients with euthyroid multinodular goiter and 83 healthy subjects without thyroid disease. The demographics, thyroid hormone levels, and thyroid ultrasonography of the participants were recorded. Venous blood samples were centrifuged and sera samples were stored at -80°C until analysis of selenium, zinc, and copper levels. The levels of trace elements were determined by inductively coupled plasma-mass spectrometry (ICP-MS).Results:While serum, zinc, and selenium levels were significantly higher in the control group than the nodular goiter group, the copper levels were similar in the two groups. Trace elements were not correlated with thyroid hormone levels and thyroid volumes. Patients in the nodular goiter group were analyzed according to their solitary and multiple nodule status. The solitary and multiple nodular goiter groups were similar in terms of copper, zinc, and selenium levels.Conclusions:Deficiency of selenium and zinc may be associated with nodular goiter. Replacement of these trace elements may be useful for the prevention of nodular goiter, especially in deficient regions.

A Rapidly Enlarging Neck Mass in a 54-Year-Old Woman

A 54-year-old woman presented to the emergency room with dyspnea, hoarseness, dysphagia, and anterior neck swelling of 2 weeks. Her past medical history was significant for a thyroid nodule status post fine needle aspiration showing lymphocytic thyroiditis and Hashimoto hypothyroidism, which was treated with 125 μg of levothyroxine daily. Family history was noncontributory. Physical examination showed that she was in acute distress, with dyspnea and biphasic stridor, a heart rate of 88 bpm, blood pressure of 130/80 mm Hg, oxygen saturation of 92% in room air, and temperature of 98.5°F.

Assessment of Integrated Classifier’s Ability to Distinguish Benign From Malignant Lung Nodules: Extended Analyses and 2-Year Follow-Up Results of the PANOPTIC (Pulmonary Nodule Plasma Proteomic Classifier) Trial

Assessment of Integrated Classifier’s Ability to Distinguish Benign From Malignant Lung Nodules: Extended Analyses and 2-Year Follow-Up Results of the PANOPTIC (Pulmonary Nodule Plasma Proteomic Classifier) Trial

Corrigendum: Machine Learning and Feature Selection Methods for Disease Classification With Application to Lung Cancer Screening Image Data

[This corrects the article DOI: 10.3389/fonc.2019.01393.].

Machine Learning and Feature Selection Methods for Disease Classification With Application to Lung Cancer Screening Image Data.

As awareness of the habits and risks associated with lung cancer has increased, so has the interest in promoting and improving upon lung cancer screening procedures. Recent research demonstrates the benefits of lung cancer screening; the National Lung Screening Trial (NLST) found as its primary result that preventative screening significantly decreases the death rate for patients battling lung cancer. However, it was also noted that the false positive rate was very high (>94%).In this work, we investigated the ability of various machine learning classifiers to accurately predict lung cancer nodule status while also considering the associated false positive rate. We utilized 416 quantitative imaging biomarkers taken from CT scans of lung nodules from 200 patients, where the nodules had been verified as cancerous or benign. These imaging biomarkers were created from both nodule and parenchymal tissue. A variety of linear, nonlinear, and ensemble predictive classifying models, along with several feature selection methods, were used to classify the binary outcome of malignant or benign status. Elastic net and support vector machine, combined with either a linear combination or correlation feature selection method, were some of the best-performing classifiers (average cross-validation AUC near 0.72 for these models), while random forest and bagged trees were the worst performing classifiers (AUC near 0.60). For the best performing models, the false positive rate was near 30%, notably lower than that reported in the NLST.The use of radiomic biomarkers with machine learning methods are a promising diagnostic tool for tumor classification. The have the potential to provide good classification and simultaneously reduce the false positive rate.

Clinical impact of variability on CT radiomics and suggestions for suitable feature selection: a focus on lung cancer

BackgroundRadiomics suffers from feature reproducibility. We studied the variability of radiomics features and the relationship of radiomics features with tumor size and shape to determine guidelines for optimal radiomics study.MethodsWe dealt with 260 lung nodules (180 for training, 80 for testing) limited to 2 cm or less. We quantified how voxel geometry (isotropic/anisotropic) and the number of histogram bins, factors commonly adjusted in multi-center studies, affect reproducibility. First, features showing high reproducibility between the original and isotropic transformed voxel settings were identified. Second, features showing high reproducibility in various binning settings were identified. Two hundred fifty-two features were computed and features with high intra-correlation coefficient were selected. Features that explained nodule status (benign/malignant) were retained using the least absolute shrinkage selector operator. Common features among different settings were identified, and the final features showing high reproducibility correlated with nodule status were identified. The identified features were used for the random forest classifier to validate the effectiveness of the features. The properties of the uncalculated feature were inspected to suggest a tentative guideline for radiomics studies.ResultsNine features showing high reproducibility for both the original and isotropic voxel settings were selected and used to classify nodule status (AUC 0.659–0.697). Five features showing high reproducibility among different binning settings were selected and used in classification (AUC 0.729–0.748). Some texture features are likely to be successfully computed if a nodule was larger than 1000 mm3.ConclusionsFeatures showing high reproducibility among different settings correlated with nodule status were identified.

Surgical Outcomes and Prognostic Factors in Cervical Cancer: A 12 year, Single-center Experience

Objective: This study was conducted to evaluate the surgical outcomes of patients with early-stage cervical cancer and to identify clinicopathological factors that may predict a 5-year disease-free survival of patients who are treated with modified or radical hysterectomies and pelvic lymphadenectomy.Methods: The record of 146 patients with early-stage invasive cervical carcinoma who had been treated at the HRH Princess Maha Chakri Sirindhorn Medical Center, in the period between January 2003 and December 2014 were retrospectively reviewed. Clinical and pathological variables that include age, wait time to surgery, stage of cancer, pelvic nodule status, lymphovascular space invasion, histology, depth of invasion, tumor grade, surgical margin status, parametrium involvement, and tumor size were recorded. The Kaplan-Meier statistical method was used for the calculation for the 5-year disease-free survival and the 5-year overall survival. The Log-rank test and Cox regression analysis were used to assess the significant factors relating to recurrence.Result: A Large population in this study was in Stage IB1 (62%). The most common histology obtained was of squamous cell carcinoma (68%). Approximately 77% of the patients underwent either a modified or radical hysterectomy and 25% had received adjuvant treatment. The median time of patient follows up was 60 months. The estimated 5-year disease-free survival of the patients with early-stage cervical cancer was 84%. Recurrent disease occurred in 14% of the patients and the majority of these (71%) were localized metastases. Stage, nodular status and tumor size were significant as poor prognostic factors resulting from the univariate analysis study. However, there were no statistically significant associations between these factors and the 5-year DFS on multivariable analysis. Conclusion: Early stage cervical cancer patients treated at our institute had favorable outcomes. The significant prognostic factors for disease-free survival were the stage, nodular status, and tumor size.&#x0D;

Laryngeal ultrasound and pediatric vocal fold nodules.

The term vocal fold nodules refers to bilateral thickening of the membranous folds with minimal impairment of the vibratory properties of the mucosa. Nodules are thought to be related to repetitive mechanical stress, associated with voice use patterns. Diagnosis is typically made in the office via either rigid or flexible laryngeal stroboscopy. Depending on the individual child, obtaining an optimal view of the larynx can be difficult if not impossible. Recent advances in high-frequency ultrasonography allows for transcervical examination of laryngeal structures. The goal of this project was to determine if laryngeal ultrasound (LUS) can be used to identify vocal fold nodules in dysphonic children. Prospective case-control study in which the patient acted as his or her own control. Forty-six pediatric patients were recruited for participation in this study; the mean age was 4.8 years. Twenty-three did not have any vocal fold lesions and 23 had a diagnosis of vocal fold nodules on laryngeal stroboscopy. Recorded LUSs were reviewed by two pediatric radiologists who were blinded to the nodule status. There was substantial inter-rater agreement (κ = 0.70, 95% confidence interval [CI]: 0.50-0.89) between the two radiologists regarding the presence of nodules. There was also substantial agreement (κ = 0.87, 95% CI: 0.72-1) between LUS and laryngeal stroboscopy. Sensitivity of LUS was 100% (95% CI: 85%-100%) and specificity was 87% (95% CI: 66%-97%). LUS can be used to identify vocal fold nodules in children with substantial agreement with laryngeal stroboscopy. 3b Laryngoscope, 127:676-678, 2017.

247 MCL-1 IS A NEW P53 FAMILY TARGET GENE IN HEPATOCELLULAR CARCINOMA

localization of c-Jun was quantified using image processing software HistoQuestTM (TissueGnostics GmbH, Vienna, Austria). The relation between nuclear c-Jun and clinical parameters was analysed. Results: Nuclear c-jun was independent on nodule status or vascular invasion. However, stage IV tumours had higher nuclear c-Jun as compared to stages I, II and III (14.8±1.9% vs 10.7±1.3%, p = 0.04). c-Jun was also increased in less differentiated G3 tumours as compared to G1 and G2 tumours (11.98±1.240 vs 17.70±3.969, p = 0.03). Both tumour diameter and ki67 positively correlated with nuclear c-Jun accumulation (r = 0.13, p = 0.05 and r = 0.18, p = 0.02 respectively). Nuclear c-Jun tended to be higher in patients with tumor recurrence after OLT without reaching statistical significance (14.62±2% vs 12.09±1.5%, p = 0.06). In addition, patients with low nuclear c-Jun staining survive longer than those with high c-Jun staining (63 vs. 23 months, p < 0.05). Conclusions: Nuclear c-Jun translocation in tumour tissue seems to confer a more malignant phenotype of HCC and could be an additional marker of HCC prognosis.

Effects of defoliation on carbohydrate status, nodules and spring growth in white clover in a sub-arctic climate

In order to improve the basis for utilizing white clover (Trifolium repens L) in northern agriculture, we studied the effects of defoliation intensity on spring growth in a sub-arctic climate in relation to carbohydrate and nodule status. White clover plants (cv Snowy) were studied in a pot experiment in the field on the coast of northern Norway from spring 2001 until spring 2002. The experiment was repeated with some modifications from spring 2002 until spring 2003. During the growing season from summer to autumn, the plants were totally stripped of leaves down to the stolon, cut at four or seven cm height or left undisturbed. The plants were sampled destructively in autumn, early spring and late spring and sorted into leaves, stolons and roots. The plant material was weighed and analysed for carbohydrate reserves and nodule number. Defoliation during the growing season resulted in reduced concentration of reserve carbohydrates in autumn and reduced winter survival of the stolons. The most severe defoliation treatment reduced the herbage growth in spring. In contrast, the two milder defoliation treatments had no effect on herbage growth during spring or on total plant dry matter and nodule status in late spring. In conclusion, moderate defoliation during the growing season had no effect on herbage growth the following spring nor on carbohydrate, nodule or dry matter status of the plant in late spring. Moderate defoliation increased spring growth and thereby also the nitrogen demand of the plants. This probably enhanced nodule formation and development of inactive to active nodules.

Genetic Polymorphisms in the EGFR (R521K) and Estrogen Receptor (T594T) Genes, EGFR and ErbB‐2 Protein Expression, and Breast Cancer Risk in Tunisia

We evaluated the association of epidermal growth factor receptor (EGFR) 142285G>A (R521K) and estrogen receptor alpha (ESR1) 2014G>A (T594T) single nucleotide polymorphisms with breast cancer risk and prognosis in Tunisian patients. EGFR 142285G>A and ESR1 2014G>A were genotyped in a sample of 148 Tunisian breast cancer patients and 303 controls using PCR-RFLP method. Immunohistochemitsry was used to evaluate the expression levels of EGFR, HER2, ESR1, progesterone receptor and BCL2 in tumors. We found no evidence for an association between EGFR R521K polymorphism and breast cancer risk. However, we found that the homozygous GG (Arg) genotype was more prevalent in patients with lymph node metastasis (P = .03) and high grade tumors (P = .011). The ESR1 2014G allele showed significant association with breast cancer risk (P = .025). The GG genotype was associated with HER2 overexpression and this association withstood univariate and multivariate analyses (P = .009; P = .021, resp.). These data suggest that the R521K might be a prognostic factor, because it correlates with both tumor grade and nodule status. The higher expression of HER2 in ESR1 T594T GG patients suggests the possibility that ESR1 gene polymorphisms accompanied by HER2 expression might influence the pathogenesis of breast cancers.