Detailed pathological examination of completion node dissection specimens and outcome in melanoma patients with minimal (<0.1 mm) sentinel lymph node metastases

Exploration and validation of key genes associated with early lymph node metastasis in thyroid carcinoma using weighted gene co-expression network analysis and machine learning

Background

Thyroid carcinoma (THCA), the most common endocrine neoplasm, typically exhibits an indolent behavior. However, in some instances, lymph node metastasis (LNM) may occur in the early stages, with the underlying mechanisms not yet fully understood.

Materials and methods

LNM potential was defined as the tumor's capability to metastasize to lymph nodes at an early stage, even when the tumor volume is small. We performed differential expression analysis using the 'Limma' R package and conducted enrichment analyses using the Metascape tool. Co-expression networks were established using the 'WGCNA' R package, with the soft threshold power determined by the 'pickSoftThreshold' algorithm. For unsupervised clustering, we utilized the 'ConsensusCluster Plus' R package. To determine the topological features and degree centralities of each node (protein) within the Protein-Protein Interaction (PPI) network, we used the CytoNCA plugin integrated with the Cytoscape tool. Immune cell infiltration was assessed using the Immune Cell Abundance Identifier (ImmuCellAI) database. We applied the Least Absolute Shrinkage and Selection Operator (LASSO), Support Vector Machine (SVM), and Random Forest (RF) algorithms individually, with the 'glmnet,' 'e1071,' and 'randomForest' R packages, respectively. Ridge regression was performed using the 'oncoPredict' algorithm, and all the predictions were based on data from the Genomics of Drug Sensitivity in Cancer (GDSC) database. To ascertain the protein expression levels and subcellular localization of genes, we consulted the Human Protein Atlas (HPA) database. Molecular docking was carried out using the mcule 1-click Docking server online. Experimental validation of gene and protein expression levels was conducted through Real-Time Quantitative PCR (RT-qPCR) and immunohistochemistry (IHC) assays.

Results

Through WGCNA and PPI network analysis, we identified twelve hub genes as the most relevant to LNM potential from these two modules. These 12 hub genes displayed differential expression in THCA and exhibited significant correlations with the downregulation of neutrophil infiltration, as well as the upregulation of dendritic cell and macrophage infiltration, along with activation of the EMT pathway in THCA. We propose a novel molecular classification approach and provide an online web-based nomogram for evaluating the LNM potential of THCA (http://www.empowerstats.net/pmodel/?m=17617_LNM). Machine learning algorithms have identified ERBB3 as the most critical gene associated with LNM potential in THCA. ERBB3 exhibits high expression in patients with THCA who have experienced LNM or have advanced-stage disease. The differential methylation levels partially explain this differential expression of ERBB3. ROC analysis has identified ERBB3 as a diagnostic marker for THCA (AUC=0.89), THCA with high LNM potential (AUC=0.75), and lymph nodes with tumor metastasis (AUC=0.86). We have presented a comprehensive review of endocrine disruptor chemical (EDC) exposures, environmental toxins, and pharmacological agents that may potentially impact LNM potential. Molecular docking revealed a docking score of -10.1 kcal/mol for Lapatinib and ERBB3, indicating a strong binding affinity.

Conclusion

In conclusion, our study, utilizing bioinformatics analysis techniques, identified gene modules and hub genes influencing LNM potential in THCA patients. ERBB3 was identified as a key gene with therapeutic implications. We have also developed a novel molecular classification approach and a user-friendly web-based nomogram tool for assessing LNM potential. These findings pave the way for investigations into the mechanisms underlying differences in LNM potential and provide guidance for personalized clinical treatment plans.

Is the non-sentinel lymph node compartment the next site for melanoma progression from the sentinel lymph node compartment in the regional nodal basin?

Melanoma patients with additional positive lymph nodes in the completion lymph node dissection (CLND) following a positive sentinel lymph node (SLN) biopsy would have a poorer prognosis than patients with no additional positive lymph nodes. We hypothesize that the progression of disease from the SLN to the non-SLN compartment is orderly and is associated with the worsening of the disease status. Thus, the SLN and non-SLN compartments are biologically different in that cancer cells, in general, arrive in the SLN compartment before spreading to the non-SLN compartment. To validate this concept, we used a large cohort of melanoma patients from our prospective SLN database in an academic tertiary medical center. Adult cutaneous melanoma patients (n = 291) undergoing CLND after a positive SLN biopsy from 1994 to 2009 were analyzed. Comparison of 5-year disease-free survival and 5-year overall survival between positive (n = 66) and negative (n = 225) CLND groups was made. The 5-year disease-free survival rates were 55% (95% CI 49-62%) for patients with no additional LN on CLND versus 14% (95% CI 8-26%) in patients with positive LN on CLND (p < 0.0001, log-rank test). The median disease-free survival time was 7.4 years with negative CLND (95% CI 4.4-15+ years) and 1.2 years with positive CLND (95% CI 1.0-1.8 years). The 5-year overall survival rates were 67% (95% CI 61-74%) for negative CLND versus 38% (95% CI 28-52%) for positive CLND (p < 0.0001, log-rank test). The median overall survival time was 12.1 years for negative CLND (95% CI 9.3-15+ years) and 2.5 years for positive CLND (95% CI 2.2-5.7 years). This study shows that CLND status is a significant prognostic factor for patients with positive SLNs undergoing CLND. Also, it suggests an orderly progression of metastasis from the SLN to the non-SLN compartment. Thus, the SLN in the regional nodal basin draining the primary melanoma may serve as an important gateway for metastasis to the non-SLN compartment and beyond to the systemic sites.

Measuring the quality of melanoma surgery - Highlighting issues with standardization and quality assurance of care in surgical oncology

In an attempt to ensure high standards of cancer care, there is increasing interest in determining and monitoring the quality of interventions in surgical oncology. In recent years, this has been particularly the case for melanoma surgery. The vast majority of patients with melanoma undergo surgery. Usually, this is with combinations of wide excision, sentinel lymph node biopsy and lymphadenectomy. The indications for these procedures evolved during a time when no effective systemic adjuvant therapy was available, and whilst the rationale has been sound, the justification for differences in extent and thoroughness has generally been supported by inadequate or low-level evidence. This has led to a substantial variation among melanoma centres or even among surgeons within a centre in how these procedures are done. With recent rapid progress in the efficacy of systemic treatments that are impacting on overall survival, the prospect of long-term survival in these previously high risk patients means that more than ever long-term locoregional control of melanoma is imperative. Furthermore, the understanding of effects of systemic therapy on locoregional disease will only be interpretable if surgeons use standardized, high quality techniques. This article focuses on standardization and evolution of quality indicators for melanoma surgery and how these might have a positive impact on patient care.

Multimodal hybrid imaging agents for sentinel node mapping as a means to (re)connect nuclear medicine to advances made in robot-assisted surgery

Purpose

Radical prostatectomy and complementary extended pelvic lymph node dissection (ePLND) of sentinel lymph nodes (SNs) and non-sentinel lymph nodes (LNs) at risk of containing metastases are increasingly being performed using high-tech robot-assisted approaches. Although this technological evolution has clear advantages, the physical nature of robotic systems limits the integrated use of routine radioguided surgery technologies. Hence, engineering effort in robotics are focused on the integration of fluorescence guidance technologies. Using the hybrid SN tracer indocyanine green-^99mTc-nanocolloid (radioactive and fluorescent), for the first time in combination with a robot-integrated laparoscope, we investigated whether the robot-assisted approach affects the accuracy of fluorescence detection of SNs identified preoperatively using nuclear medicine.

Methods

The study included 55 patients (Briganti nomogram-based risk >5 % on LN metastases) scheduled for robot-assisted radical prostatectomy, SN biopsy and ePLND. Following indocyanine green-^99mTc-nanocolloid injection, preoperative nuclear imaging (lymphoscintigraphy and SPECT/CT) was used to locate the SN(s). The fluorescence laparoscope was used intraoperatively to identify the SN(s) with standard fluorescence settings (in 50 patients) and with customized settings (in 5 patients). The number and location of the SNs, the radioactive, fluorescence (both in vivo and ex vivo) and tumour status of the resected SNs/LNs, and postoperative complications were recorded and analysed.

Results

Combined, preoperative lymphoscintigraphy and SPECT/CT imaging identified 212 SNs (median 4 per patient). Intraoperative fluorescence imaging using standard fluorescence settings visualized 80.4 % (148/184 SNs; 50 patients; ex vivo 97.8 %). This increased to 85.7 % (12/14 SNs; 5 patients; ex vivo 100 %) with customized fluorescence settings. SPECT/CT images provided guidance towards the residual SNs. Ex vivo all removed SNs were radioactive. SNs were tumour-positive in 25.4 % of patients (14/55; false-negative rate 7 %, 1/14 patients). In ten patients, the SN was the only tumour-positive LN. Surgical complications were minimal.

Conclusion

Directly linking 3D preoperative nuclear imaging information on SNs to a robot-integrated fluorescence laparoscope improved the surgeon’s use of the technology and did not influence the sensitivity or morbidity of the procedure. To our surprise, however, the detection rates with the current fluorescence camera did not improve.