Oral cancer: changing the aim of the biopsy in the age of precision medicine. A review

Unraveling the role of disulfidptosis-related LncRNAs in colon cancer: a prognostic indicator for immunotherapy response, chemotherapy sensitivity, and insights into cell death mechanisms

Background: Colon cancer, a prevalent and deadly malignancy worldwide, ranks as the third leading cause of cancer-related mortality. Disulfidptosis stress triggers a unique form of programmed cell death known as disulfidoptosis, characterized by excessive intracellular cystine accumulation. This study aimed to establish reliable bioindicators based on long non-coding RNAs (LncRNAs) associated with disulfidptosis-induced cell death, providing novel insights into immunotherapeutic response and prognostic assessment in patients with colon adenocarcinoma (COAD). Methods: Univariate Cox proportional hazard analysis and Lasso regression analysis were performed to identify differentially expressed genes strongly associated with prognosis. Subsequently, a multifactorial model for prognostic risk assessment was developed using multiple Cox proportional hazard regression. Furthermore, we conducted comprehensive evaluations of the characteristics of disulfidptosis response-related LncRNAs, considering clinicopathological features, tumor microenvironment, and chemotherapy sensitivity. The expression levels of prognosis-related genes in COAD patients were validated using quantitative real-time fluorescence PCR (qRT-PCR). Additionally, the role of ZEB1-SA1 in colon cancer was investigated through CCK8 assays, wound healing experiment and transwell experiments. Results: disulfidptosis response-related LncRNAs were identified as robust predictors of COAD prognosis. Multifactorial analysis revealed that the risk score derived from these LncRNAs served as an independent prognostic factor for COAD. Patients in the low-risk group exhibited superior overall survival (OS) compared to those in the high-risk group. Accordingly, our developed Nomogram prediction model, integrating clinical characteristics and risk scores, demonstrated excellent prognostic efficacy. In vitro experiments demonstrated that ZEB1-SA1 promoted the proliferation and migration of COAD cells. Conclusion: Leveraging medical big data and artificial intelligence, we constructed a prediction model for disulfidptosis response-related LncRNAs based on the TCGA-COAD cohort, enabling accurate prognostic prediction in colon cancer patients. The implementation of this model in clinical practice can facilitate precise classification of COAD patients, identification of specific subgroups more likely to respond favorably to immunotherapy and chemotherapy, and inform the development of personalized treatment strategies for COAD patients based on scientific evidence.

An Intelligent System to Improve Diagnostic Support for Oral Squamous Cell Carcinoma

Oral squamous cell carcinoma (OSCC) is one of the most-prevalent cancer types worldwide, and it poses a serious threat to public health due to its high mortality and morbidity rates. OSCC typically has a poor prognosis, significantly reducing the chances of patient survival. Therefore, early detection is crucial to achieving a favorable prognosis by providing prompt treatment and increasing the chances of remission. Salivary biomarkers have been established in numerous studies to be a trustworthy and non-invasive alternative for early cancer detection. In this sense, we propose an intelligent system that utilizes feed-forward artificial neural networks to classify carcinoma with salivary biomarkers extracted from control and OSCC patient samples. We conducted experiments using various salivary biomarkers, ranging from 1 to 51, to train the model, and we achieved excellent results with precision, sensitivity, and specificity values of 98.53%, 96.30%, and 97.56%, respectively. Our system effectively classified the initial cases of OSCC with different amounts of biomarkers, aiding medical professionals in decision-making and providing a more-accurate diagnosis. This could contribute to a higher chance of treatment success and patient survival. Furthermore, the minimalist configuration of our model presents the potential for incorporation into resource-limited devices or environments.

Correlation between radiologic depth of invasion and pathologic depth of invasion in oral cavity squamous cell carcinoma: A systematic review and meta-analysis

OBJECTIVES

To comprehensively assess the correlation between radiologic depth of invasion (rDOI) and pathologic depth of invasion (pDOI) in oral cavity squamous cell carcinoma (OSCC) by meta-analysis.

MATERIALS AND METHODS

PubMed and Embase databases were searched to find pertinent articles reporting rDOI of OSCC. Studies evaluating the correlations and mean differences (MDs) between rDOI and pDOI were included. The rDOI was measured based on ultrasound (US), computed tomography (CT), or magnetic resonance imaging (MRI). The correlation coefficients and MDs between rDOI and pDOI were meta-analytically pooled. Between-study heterogeneity was assessed using Higgins' inconsistency index (I²). Subgroup analysis was performed based on imaging modality.

RESULTS

Twenty-three studies with 1787 patients were included. The pooled correlation coefficient and MD were 0.86 (95 % confidence interval [CI], 0.82-0.90; I² = 66.9 %) and 1.84 mm (95 % CI, 1.02-2.65 mm; I² = 88.2 %), respectively. In subgroup analysis, MRI showed the largest MD (n = 12, 2.61 mm), followed by US (n = 2, -0.41 mm) and CT (n = 2, 0.12 mm). US showed the highest correlation coefficient (n = 3, 0.91), followed by MRI (n = 12, 0.85) and CT (n = 3, 0.82).

CONCLUSION

rDOI measured by US, CT, and MRI demonstrated excellent correlations with pDOI.

Neck Management in cT1N0 Tongue Squamous Cell Carcinoma as Determined by Sonographic Depth of Invasion

Objectives

To compare the oncologic outcomes in patients with cT1N0 tongue squamous cell carcinoma (SCC) who underwent different neck management strategies stratified by sonographic depth of invasion (DOI).

Methods

The included patients were retrospectively enrolled, and divided into two groups: observation (OBS) and elective neck dissection (END). The regional control (RC) and disease-specific survival (DSS) rates were compared and stratified by sonographic DOI.

Results

The mean sonographic and pathologic DOIs were 3.8 and 3.7 mm, respectively; the two DOIs were significantly correlated (Spearman correlation coefficient 0.974. p <0.001). In patients with sonographic DOI <4.0 mm, the 5-year RC rates were 73 and 89% in the OBS and END groups, respectively, and were not significantly different. However, in patients with sonographic DOI ≥4.0 mm, the 5-year RC rate was significantly different between the OBS (57%) and END (80%) groups (p = 0.031). In patients with sonographic DOI <4.0 mm, the 5-year DSS rates were 79 and 89% in OBS and END groups, respectively, and were not significantly different. However, in patients with sonographic DOI ≥4.0 mm, the 5-year DSS rate was significantly different between the OBS (67%) and END (86%) groups (p = 0.033).

Conclusions

Sonographic DOI was notably correlated with pathologic DOI. Moreover, there was a significant survival difference between the OBS and END groups in cT1N0 tongue SCC patients with sonographic DOI ≥4.0 mm but not in those with sonographic DOI <4.0 mm. Our study provides a useful method to aid decision-making in the clinical setting for this patient group.