Identification of biomarkers associated with cervical lymph node metastasis in papillary thyroid carcinoma: Evidence from an integrated bioinformatic analysis

Optimizing Bi-LSTM networks for improved lung cancer detection accuracy

Lung cancer remains a leading cause of cancer-related deaths worldwide, with low survival rates often attributed to late-stage diagnosis. To address this critical health challenge, researchers have developed computer-aided diagnosis (CAD) systems that rely on feature extraction from medical images. However, accurately identifying the most informative image features for lung cancer detection remains a significant challenge. This study aimed to compare the effectiveness of both hand-crafted and deep learning-based approaches for lung cancer diagnosis. We employed traditional hand-crafted features, such as Gray Level Co-occurrence Matrix (GLCM) features, in conjunction with traditional machine learning algorithms. To explore the potential of deep learning, we also optimized and implemented a Bidirectional Long Short-Term Memory (Bi-LSTM) network for lung cancer detection. The results revealed that the highest performance using hand-crafted features was achieved by extracting GLCM features and utilizing Support Vector Machine (SVM) with different kernels, reaching an accuracy of 99.78% and an AUC of 0.999. However, the deep learning Bi-LSTM network surpassed both methods, achieving an accuracy of 99.89% and an AUC of 1.0000. These findings suggest that the proposed methodology, combining hand-crafted features and deep learning, holds significant promise for enhancing early lung cancer detection and ultimately improving diagnosis systems.

Elevated Levels of Interleukin-18 are Associated with Lymph Node Metastasis in Papillary Thyroid Carcinoma

Interleukin-18 (IL-18) is a proinflammatory cytokine that primarily stimulates the Th1 immune response. IL-18 exhibits anticancer activity and has been evaluated in clinical trials as a potential cancer treatment. However, evidence suggests that it may also facilitate the development and progression of some cancers. So far, the impact of IL-18 on papillary thyroid cancer (PTC) has not been investigated. In this study, we found that the expression of IL-18 was significantly increased in PTC compared to normal thyroid tissue. Elevated IL-18 expression was closely associated with lymphovascular invasion and lymph node metastases. Furthermore, compared to PTC patients with no nodal metastasis, serum IL-18 levels were slightly increased in patients with 1-4 nodal metastases and significantly elevated in patients with 5 or more nodal metastases. The pro-metastatic effect of IL-18 may be attributed to the simultaneous increase in the expression of S100A10, a known factor that is linked to nodal metastasis in PTC. In addition, the activation of several pathways, such as the intestinal immune network for lgA production and Staphylococcus aureus infection, may be involved in the metastasis process. Taken together, IL-18 may trigger pro-metastatic activity in PTC. Therefore, suppressing the function of IL-18 rather than enhancing it appears to be a reasonable strategy for treating aggressive PTC.

Sonographic characteristics and clinical characteristics combined with nomogram for predicting the aggressiveness of papillary thyroid carcinoma coexisted with Hashimoto's thyroiditis

OBJECTIVE

The association between Papillary Thyroid Carcinoma (PTC) and coexistent Hashimoto's Thyroiditis (HT) was controversial. The purpose of this study was to evaluate the presence of HT exerts any influence on the aggressiveness of PTC, and to establish a nomogram for predicting the possibility of aggressiveness in PTC.

METHODS

373 consecutive PTC patients with/without coexistent HT from January 2017 to December 2020 were retrospective reviewed. Patients' clinicopathologic and sonographic characteristics were collected for univariate and multivariate analyses. A nomogram was established based on the risk factors for aggressiveness in PTC.

RESULTS

Male (p = 0.001), tumor size >1.0 cm (p = 0.046) and lymph node metastasis (p = 0.018) were negatively associated with PTC coexisted with HT, while it was significantly positively associated with the frequence of multifocality (p = 0.010). Univariate and multivariate analyses suggested that age ≥55 years (p = 0.000), male (p = 0.027), HT (p = 0.017), tumor size >1.0 cm (p = 0.015), multifocality (p = 0.041), distance to capsular ≤0 cm (p = 0.050) and blood flow (Grade I: p = 0.044) were independent risk factors for predicting the aggressiveness in PTC. A nomogram according to these predictors was further developed and validated. The receiver operating characteristic curve (AUC = 0.734 and 0.809 for training and validation cohorts, respectively) and decision curve analyses indicated that the nomogram model was clinically useful. The calibration curve revealed that the nomogram exhibited an excellent consistency.

CONCLUSIONS

In this study, the coexistent HT might play a protective role in preventing the proliferation of PTC. Dispensable aggressive treatment may be reduced in PTC by pre-operative identification of sonographic and clinical characteristics and incorporating with the predicted nomogram model.

Preoperative Prediction of Metastatic Lymph Nodes Posterior to the Right Recurrent Laryngeal Nerve in cN0 Papillary Thyroid Carcinoma

Background

The advantages of the dissecting the metastatic lymph nodes posterior to the right recurrent laryngeal nerve (LN-prRLN) remain a great deal of controversies in papillary thyroid carcinoma (PTC) patients without clinical evidence. The purpose of our retrospective research was to investigate the predictive factors of the LN-prRLN in cN0 PTC patients.

Methods and Materials

Altogether 251 consecutive cN0 PTC participants accepted unilateral or bilateral thyroidectomy accompanied with LN-prRLN dissection between June 2020 and May 2023 were included in the research. Then, univariate and multivariate logical regression analysis were conducted to analyze the relationship between the LN-prRLN and these predictive factors, and a predictive model was also developed. Surgical complications of LN-prRLN dissection were also presented.

Results

The rate of LN-prRLN was 17.9% (45/251) in cN0 PTC patients after the analysis of postoperative histology. The age <55 years, multifocality, microcalcification, and BRAFV600E mutation were identified to be predictive factors of LN-prRLN in cN0 PTC patients. The risk score for LN-prRLN was calculated: risk score = 1.192 × (if age <55 years) + 0.808 × (if multifocality) + 1.196 × (if microcalcification in nodule) + 0.918 × (if BRAFV600E mutation in nodule). The rates of the transient hypoparathyroidism and hoarseness were 1.2% (3/251) and 2.0% (5/251), respectively.

Conclusion

The age <55 years, multifocality, microcalcification, and BRAFV600E mutation are independent predictors of the LN-prRLN in cN0 PTC patients. An effective predictive model was established for predicting the LN-prRLN in cN0 PTC patients, with the aim to better guide the surgical treatment of PTC. A thorough inspection of the lateral compartment is recommended in PTC patients with risk factors. The multicenter research with long-term follow-up should be carried out to ascertain the optimal surgical approach for patients with PTC.

Role of Inflammatory Biomarkers (NLR, LMR, PLR) in the Prognostication of Malignancy in Indeterminate Thyroid Nodules

Indeterminate follicular thyroid lesions (Thyr 3A and 3B) account for 10% to 30% of all cytopathologic diagnoses, and their unpredictable behavior represents a hard clinical challenge. The possibility to preoperatively predict malignancy is largely advocated to establish a tailored surgery, preventing diagnostic thyroidectomy. We analyzed the role of the neutrophil-to-lymphocyte ratio (NLR), the platelet-to-lymphocyte ratio (PLR) and the lymphocyte-to-monocyte ratio (LMR) as prognostic factors of malignancy for indeterminate thyroid nodules. In patients affected by cytological Thyr 3A/3B nodules, NLR, PLR and LMR were retrospectively compared and correlated with definitive pathology malignancy, utilizing student's t-test, ROC analysis and logistic regression. One-hundred and thirty-eight patients presented a Thyr 3A and 215 patients presented a Thyr 3B. After the logistic regression, in Thyr 3A, none of the variables were able to predict malignancy. In Thyr 3B, NLR prognosticated thyroid cancer with an AUC value of 0.685 (p < 0.0001) and a cut-off of 2.202. The NLR results were also similar when considering the overall cohort. The use of cytological risk stratification in addressing the management of indeterminate thyroid nodules in patients is not always reliable. NLR is an easy and reproducible inflammatory biomarker capable of improving the accuracy of preoperative prognostication of malignancy.

Initial ablation radio predicting volume reduction from microwave ablation of benign thyroid nodules

OBJECTIVE

Our research sought to investigate the relationship between initial ablation ratio (IAR) and internal composition of benign thyroid nodules treated by microwave ablation (MWA).

MATERIALS AND METHODS

Patients who underwent MWA at the Affiliated Hospital of Jiangsu University from January 2018 to December 2022 were enrolled in our research. All the patients were followed up for at least one year. We analyzed the relationship between IAR at 1 month of solid nodules (solid >90%), predominantly solid nodules (90% >solid > 75%), mixed solid alongside cystic nodules (75% >solid > 50%) as well as volume reduction rate (VRR) at 1, 3, 6 and 12 months follow-up.

OBJECTIVE

The mean IAR of the solid nodules (solid >90%) was 94.32±7.87%,#x0025;, that of the predominantly solid nodules (90% >solid > 75%) and mixed solid alongside cystic nodules (75% >solid > 50%) were 86.51±6.66% and 75.19±4.97%,#x0025;, respectively. Almost all the thyroid nodules were significantly decreased in size after MWA. After 12 months of MWA treatment, the average volume of the aforementioned thyroid nodules decreased from 8.69±8.79 to 1.84±3.11 ml, 10.94±9.07 to 2.58±3.34 ml, 9.92±6.27 to 0.25±0.42 ml, respectively. The mean symptom and cosmetic scores of the nodules showed significant (p < 0.000) improvement. The rates of the complications or side effects of MWA against the above-mentioned nodule types were 8.3% (3/36), 3.2% (1/31) and 0% (0/36), respectively.

CONCLUSIONS

The application of the IAR to quantify the success rate of thyroid nodule microwaves in the short term demonstrated that IAR was related to the internal components of the nodule. Although the IAR was not high when the thyroid component was mixed solid and cystic nodules (75% >solid > 50%), the final therapeutic effect was still satisfactory.

Virtual touch tissue imaging for differential diagnosis in ACR TI-RADS category 3-4 thyroid nodules: Conservative and aggressive methods

PURPOSE

Many Thyroid Imaging Reporting and Data System (TI-RADS) category 3-4 nodules are benign. Our study aimed to add virtual touch tissue imaging (VTI) to TI-RADS using two methods, namely conservative and aggressive, and to explore which method had better diagnostic performance and which method avoided more unnecessary biopsies.

METHODS

From January 2016 to December 2021, we included 121 thyroid nodules classified as TI-RADS category 3-4 in 115 consecutive patients in this retrospective study. This study used the reference standard for pathological diagnosis by surgical resection or biopsy. The diagnostic performance of the different methods was evaluated and compared by receiver operating characteristic (ROC) and area under the ROC curve (AUC).

RESULTS

In this study, the aggressive approach had the best diagnostic performance among TI-RADS alone, the conservative approach, and the aggressive approach (AUC: 0.863 versus 0.598, P = 0.0007; 0.863 versus 0.755, P = 0.0067). When we used an aggressive approach, 75.44% (43/57) of the 57 false-positive nodes diagnosed by TI-RADS were appropriately downgraded from TI-RADS category 4 to category 3, avoiding unnecessary biopsies.

CONCLUSION

VTI improves the diagnostic performance of TI-RADS. The aggressive approach of combining the TI-RADS with VTI would help reduce unnecessary biopsies.

Metadata analysis to explore hub of the hub-genes highlighting their functions, pathways and regulators for cervical cancer diagnosis and therapies

Cervical cancer (CC) is considered as the fourth most common women cancer globally.that shows malignant features of local infiltration and invasion into adjacent organs and tissues. There are several individual studies in the literature that explored CC-causing hub-genes (HubGs), however, we observed that their results are not so consistent. Therefore, the main objective of this study was to explore hub of the HubGs (hHubGs) that might be more representative CC-causing HubGs compare to the single study based HubGs. We reviewed 52 published articles and found 255 HubGs/studied-genes in total. Among them, we selected 10 HubGs (CDK1, CDK2, CHEK1, MKI67, TOP2A, BRCA1, PLK1, CCNA2, CCNB1, TYMS) as the hHubGs by the protein-protein interaction (PPI) network analysis. Then, we validated their differential expression patterns between CC and control samples through the GPEA database. The enrichment analysis of HubGs revealed some crucial CC-causing biological processes (BPs), molecular functions (MFs) and cellular components (CCs) by involving hHubGs. The gene regulatory network (GRN) analysis identified four TFs proteins and three miRNAs as the key transcriptional and post-transcriptional regulators of hHubGs. Then, we identified hHubGs-guided top-ranked FDA-approved 10 candidate drugs and validated them against the state-of-the-arts independent receptors by molecular docking analysis. Finally, we investigated the binding stability of the top-ranked three candidate drugs (Docetaxel, Temsirolimus, Paclitaxel) by using 100 ns MD-based MM-PBSA simulations and observed their stable performance. Therefore the finding of this study might be the useful resources for CC diagnosis and therapies.

Bioinformatics Screening of Potential Biomarkers from mRNA Expression Profiles to Discover Drug Targets and Agents for Cervical Cancer

Bioinformatics analysis has been playing a vital role in identifying potential genomic biomarkers more accurately from an enormous number of candidates by reducing time and cost compared to the wet-lab-based experimental procedures for disease diagnosis, prognosis, and therapies. Cervical cancer (CC) is one of the most malignant diseases seen in women worldwide. This study aimed at identifying potential key genes (KGs), highlighting their functions, signaling pathways, and candidate drugs for CC diagnosis and targeting therapies. Four publicly available microarray datasets of CC were analyzed for identifying differentially expressed genes (DEGs) by the LIMMA approach through GEO2R online tool. We identified 116 common DEGs (cDEGs) that were utilized to identify seven KGs (AURKA, BRCA1, CCNB1, CDK1, MCM2, NCAPG2, and TOP2A) by the protein–protein interaction (PPI) network analysis. The GO functional and KEGG pathway enrichment analyses of KGs revealed some important functions and signaling pathways that were significantly associated with CC infections. The interaction network analysis identified four TFs proteins and two miRNAs as the key transcriptional and post-transcriptional regulators of KGs. Considering seven KGs-based proteins, four key TFs proteins, and already published top-ranked seven KGs-based proteins (where five KGs were common with our proposed seven KGs) as drug target receptors, we performed their docking analysis with the 80 meta-drug agents that were already published by different reputed journals as CC drugs. We found Paclitaxel, Vinorelbine, Vincristine, Docetaxel, Everolimus, Temsirolimus, and Cabazitaxel as the top-ranked seven candidate drugs. Finally, we investigated the binding stability of the top-ranked three drugs (Paclitaxel, Vincristine, Vinorelbine) by using 100 ns MD-based MM-PBSA simulations with the three top-ranked proposed receptors (AURKA, CDK1, TOP2A) and observed their stable performance. Therefore, the proposed drugs might play a vital role in the treatment against CC.