Report of a case with gallbladder carcinoma: P53 expression of the peritumor epithelium might predict biliary tract recurrence

Utility of IMP3, p53, and S100P immunohistochemical stains in distinguishing reactive atypia from dysplasia in cholecystectomy specimens

BACKGROUND

Distinguishing reactive atypia from dysplasia in cholecystectomy specimens can be histologically challenging. The aim of this study was to evaluate the utility of IMP3, p53, and S100P immunostains in differentiating reactive atypia from dysplasia in cholecystectomies.

METHODS

Fifty-four cholecystectomies were reviewed and characterized into 5 groups: 2 normal, 29 reactive atypia, 16 low-grade dysplasia, 2 high-grade dysplasia, and 5 adenocarcinoma. IMP3, p53, and S100P immunostains were performed and evaluated. IMP3 (nuclear) and S100P (nuclear or nuclear/cytoplasmic) were categorized into negative or positive expression, and p53 was categorized into wild-type and aberrant/mutant expression. Chi-square test was used for statistical analysis.

RESULTS

The patients were mostly middle-aged women (mean 44, range 19-87 years, 81% female), with predominantly Hispanic White ethnicity (80%). The majority of the normal and reactive atypia cases showed negative IMP3 (100% and 75.9%, respectively) and wild-type p53 (100% and 89.7%, respectively) staining. Over half (56.3%) of the low-grade dysplasia and all the high-grade dysplasia cases showed IMP3 positivity. Aberrant p53 staining pattern was seen in half of both low and high-grade dysplasia cases. Adenocarcinoma showed IMP3 positivity in 80% and p53 aberrancy in all cases. S100P showed no statistical significance among the diagnostic categories. Significant differences in staining patterns were found between reactive atypia vs. low-grade dysplasia, and reactive atypia vs. low-grade + high-grade dysplasia using a combination of IMP3 and p53 stains (all p < 0.05).

CONCLUSIONS

In challenging cholecystectomies, IMP3 positivity or aberrant p53 expression may serve as a useful adjunct to support a diagnosis of dysplasia over reactive atypia.

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.