Prediction of lymph node metastasis in oral tongue squamous cell carcinoma using the neutrophil-to-lymphocyte ratio and platelet-to-neutrophil ratio

Two Hematological Markers Predicting the Efficacy and Prognosis of Neoadjuvant Chemotherapy Using Lobaplatin Against Triple-Negative Breast Cancer

BACKGROUND

Our previous work indicated that the addition of lobaplatin to combined therapy with taxane and anthracycline can improve the pathological complete response rate of neoadjuvant therapy for triple-negative breast cancer (TNBC) and lengthen long-term survival significantly, but the therapeutic markers of this regimen are unclear.

METHODS

Eighty-three patients who met the inclusion criteria were included in this post hoc analysis. We analyzed the association between platelet-to-lymphocyte ratio (PLR) and neutrophil-to-lymphocyte ratio (NLR) before neoadjuvant chemotherapy with the efficacy and prognosis after treatment with docetaxel, epirubicin, and lobaplatin neoadjuvant chemotherapy regimen. χ2 test and Cox regression were used to analyze the association between PLR and NLR with total pathologic complete response (tpCR), as well as the association between PLR and NLR with event-free survival (EFS) and overall survival (OS), respectively.

RESULTS

The tpCR rate in the PLR- group was 49.0% (25/51), which was significantly higher than that in the PLR+ group (25.0% [8/32], P = .032). The tpCR rate in the NLR- group was 49.1% (26/53), which was significantly higher than that in the NLR+ group (23.3% [7/30], P = .024). The tpCR rate of the PLR-NLR- (PLR- and NLR-) group was 53.7% (22/41), which was significantly higher than that of the PLR+/NLR+ (PLR+ or/and NLR+) group (26.1% [11/42]; P = .012). EFS and OS in the NLR+ group were significantly shorter than those in the NLR- group (P = .028 for EFS; P = .047 for OS). Patients in the PLR-NLR- group had a longer EFS than those in the PLR+/NLR+ group (P = .002).

CONCLUSION

PLR and NLR could be used to predict the efficacy of neoadjuvant therapy with the taxane, anthracycline, and lobaplatin regimen for patients with TNBC, as patients who had lower PLR and NLR values had a higher tpCR rate and a better long-term prognosis.

Survival among treated tongue cancer patients: a single-center experience

OBJECTIVE

To describe overall survival (OS) and disease-free survival (DFS) in a cohort of tongue cancer patients, together with the corresponding demographic, tumor and surgical characteristics.

METHODS

A retrospective study was made of 205 consecutive patients with primary tongue cancer subjected to surgery and adjuvant therapy according to the stage of the disease, in Hospital Clínico Universitario Virgen de la Arrixaca (HUVA) (Murcia, Spain) during the period 2000-2020. Survival was evaluated based on the Kaplan-Meier method, and the existence of significant differences between the different study variables was analyzed using the log-rank test. Cox regression analysis was performed for the identification of risk factors.

RESULTS

In relation to overall survival, 72.6% of the patients survived for a mean time of 14.43 years [standard error (SE) = 0.74; 95% CI: 12.98-15.87], with a cumulative survival rate of 49.8 ± 3%. Survival was reduced by the presence of tumor adjacent to resection margins [hazard ratio (HR) 2.20; 95% CI 1.09-4.43] (p = 0.028) and infiltrated resection margins (HR 3.86, 95% CI 1.56-9.57) (p = 0.004). Lymphadenectomy in turn increased survival (HR 0.15; 95% CI 0.06-0.42) (p < 0.001). In relation to disease-free survival, 55.3% of the patients suffered no relapse over a mean period of 9.91 years (SE = 0.66; 95% CI: 8.61-11.2), with a cumulative survival rate of 26.6% ± 8.4%.

CONCLUSIONS

In tongue cancer patients, overall and specific survival were reduced in the presence of infiltrated resection margins. Lymphadenectomy in turn improved survival compared with patients in which this procedure was not carried out.

Predictors of Occult Metastasis and Prognostic Factors in Patients with cN0 Oral Cancer Who Underwent Elective Neck Dissection

Elective neck dissection (END) is recommended for the management of patients with oral squamous cell carcinoma (OSCC) because of the risk of occult metastasis (OM). We hypothesized that some factors predict poor prognosis regardless of a cN0 END. This study aimed to investigate the predictors of OM and prognostic factors in patients with cN0 OSCC who underwent supraomohyoid neck dissection (SOHND). A retrospective cohort study design was created and implemented. The primary predictive variables in this study were OM and risk factors for poor prognosis after SOHND. A Cox proportional hazard model was used to adjust for the effects of potential confounders on the risk factors for poor prognoses. Among 86 patients with OSCC, OMs were observed in 9 (10.5%). The neutrophil-to-lymphocyte ratio (NLR) and vascular invasion are good markers for detecting OM. A Cox multivariable analysis identified two independent predictors of overall survival: pathologic node (pN) and laterality of END. An independent predictive factor for disease-free survival, the surgical margin, was also identified in this study. According to the pN classification, pN1 patients had a worse survival rate than pN2 patients. Therefore, in the case of pN1, regardless of being cN0, additional adjuvant therapy may be necessary.

Dual-Energy Computed Tomography Parameters Combined With Inflammatory Indicators Predict Cervical Lymph Node Metastasis in Papillary Thyroid Cancer

BACKGROUND AND OBJECTIVE

Cervical lymph node metastasis (CLNM) is considered a marker of papillar Fethicy thyroid cancer (PTC) progression and has a potential impact on the prognosis of PTC. The purpose of this study was to screen for predictors of CLNM in PTC and to construct a predictive model to guide the surgical approach in patients with PTC.

METHODS

This is a retrospective study. Preoperative dual-energy computed tomography images of 114 patients with pathologically confirmed PTC between July 2019 and April 2023 were retrospectively analyzed. The dual-energy computed tomography parameters [iodine concentration (IC), normalized iodine concentration (NIC), the slope of energy spectrum curve (λHU)] of the venous stage cancer foci were measured and calculated. The independent influencing factors for predicting CLNM were determined by univariate and multivariate logistic regression analysis, and the prediction models were constructed. The clinical benefits of the model were evaluated using decision curves, calibration curves, and receiver operating characteristic curves.

RESULTS

The statistical results show that NIC, derived neutrophil-to-lymphocyte ratio (dNLR), prognostic nutritional index (PNI), gender, and tumor diameter were independent predictors of CLNM in PTC. The AUC of the nomogram was .898 (95% CI: .829-.966), and the calibration curve and decision curve showed that the prediction model had good predictive effect and clinical benefit, respectively.

CONCLUSION

The nomogram constructed based on dual-energy CT parameters and inflammatory prognostic indicators has high clinical value in predicting CLNM in PTC patients.

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.

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.

Prediction of lymph node metastasis in oral tongue squamous cell carcinoma using the neutrophil-to-lymphocyte ratio and platelet-to-neutrophil ratio

Background

Lymph node metastasis in a variety of tumors is associated with systemic inflammatory markers. However, this association has not been reported in oral tongue squamous cell carcinoma (OTSCC). This study aimed to investigate how the preoperative neutrophil‐to‐lymphocyte ratio (NLR) and platelet‐to‐neutrophil ratio (PNR) in OTSCC patients correlated with the occurrence of OTSCC and lymph node metastasis.

Methods

The data of 73 patients with primary OTSCC who underwent surgical resection were retrospectively analyzed. Patients with other malignant tumors, patients who had received radiotherapy or chemotherapy before surgery, and patients with active inflammation were excluded. The enrolled patients were divided into groups N₀ (no early‐stage lymph node metastasis) and N₁ (early‐stage lymph node metastasis). Venous blood samples were collected before surgery and at the third week after surgery and subjected to complete blood counting in a blood analyzer. Eighty‐seven healthy people were included as a control group. In addition, the NLR and PNR in OTSCC patients were compared with those in the controls, and the postoperative NLR and PNR of group N₀ were compared with those of group N₁.

Results

The NLR was significantly higher in the OTSCC patients than the controls (p < 0.05). The area under the receiver operating characteristic curve was 0.595. Further comparison of the NLR and PLR between group N₀ and group N₁ showed that when NLR was ≤1.622, and the probability of early‐stage lymph node metastasis in OTSCC patients was 73.3%, and when PNR was >60.889, the probability was 86.7%. In re‐examination 3 weeks postoperatively, the NLR and PNR were not significantly different between groups.

Conclusion

The NLR has certain reference value for the diagnosis of OTSCC. The preoperative NLR and PNR can be used to predict early‐stage lymph node metastasis in patients with histopathologically confirmed OTSCC.