p53 Immunohistochemistry Patterns Are Surrogate Biomarkers for TP53 Mutations in Gastrointestinal Neuroendocrine Neoplasms

Proteomic study of gamma-oryzanol preventive effect on a diet-induced non-alcoholic fatty liver disease model

Nonalcoholic fatty liver disease (NAFLD) is the most common liver disease associated with obesity and diabetes prevalence. The use of natural compounds has become an attractive approach to prevent NAFLD and its progression. Gamma-oryzanol (Orz) is a natural compound whose beneficial effects on chronic metabolic diseases have been reported. Therefore, we aimed to investigate the preventive effect of Orz on the hepatic proteome in a diet induced NAFLD model. Wistar rats were randomly distributed into three experimental groups (n=6/group) according to the diet received for 30 weeks: Control group, high sugar-fat (HSF) group, and HSF+Orz group. The isolated Orz was added to the chow at the dose of 0.5% (w/w). We evaluated the nutritional profile, characterized the presence of steatosis through histological analysis, triglyceride content in liver tissue and hepatic inflammation. Next, we performed label-free quantitative proteomics of hepatic tissue. Network analysis was performed to describe involved protein pathways. NAFLD induction was characterized by the presence of hepatic steatosis. Orz prevented lipid accumulation. The compound prevented alterations of the hepatic proteome, highlighted by the modulation of lipid metabolism, inflammation, oxidative stress, xenobiotic metabolism, and the sirtuin signaling pathway. It was possible to identify key altered pathways of NAFLD pathophysiology modulated by Orz which may provide insights into NAFLD treatment targets.

Accurate interpretation of p53 immunohistochemical patterns is a surrogate biomarker for TP53 alterations in large B-cell lymphoma

BACKGROUND

To clarify the relationship between p53 immunohistochemistry (IHC) staining and TP53 alterations (including mutations and deletions) in large B-cell lymphomas (LBCLs) and to explore the possibility of p53 IHC expression patterns as surrogate markers for TP53 alterations.

METHODS

A total of 95 patients diagnosed with LBCLs were selected, and paraffin samples were taken for TP53 gene sequencing, fluorescence in situ hybridization and p53 IHC staining. The results were interpreted by experienced pathologists and molecular pathologists.

RESULTS

Forty-three nonsynonymous TP53 mutations and p53 deletions were detected in 40 cases, whereas the remaining 55 cases had wild-type TP53 genes. The majority of TP53 mutations (34/43, 79.1%) occurred in exons 4-8, and R248Q was the most common mutation codon (4/43, 9.3%). The highest frequency single nucleotide variant was C > T (43.6%). p53 expression was interpreted as follows: Pattern A: p53 staining was positive in 0%-3% of tumor cells, Pattern B: p53 staining was positive in 4-65% of tumor cells, Pattern C: more than 65% of tumor cells were stained positive for p53. The p53 IHC expression patterns were associated with TP53 alterations. Gain of function variants and wild-type TP53 tended to exhibit type C and B p53 expression patterns, but loss of function variants were exclusively seen in type A cases. Additionally, interpretation of the staining by various observers produced significant reproducibility.

CONCLUSIONS

The p53 IHC expression patterns can be used to predict TP53 alterations and are reliable for diverse alteration types, making them possible surrogate biomarkers for TP53 alterations in LBCLs.

Real-world routine diagnostic molecular analysis for TP53 mutational status is recommended over p53 immunohistochemistry in B-cell lymphomas

Previous studies in patients with mature B-cell lymphomas (MBCL) have shown that pathogenic TP53 aberrations are associated with inferior chemotherapeutic efficacy and survival outcomes. In solid malignancies, p53 immunohistochemistry is commonly used as a surrogate marker to assess TP53 mutations, but this correlation is not yet well-established in lymphomas. This study evaluated the accuracy of p53 immunohistochemistry as a surrogate marker for TP53 mutational analysis in a large real-world patient cohort of 354 MBCL patients within routine diagnostic practice. For each case, p53 IHC was assigned to one of three categories: wild type (staining 1-50% of tumor cells with variable nuclear staining), abnormal complete absence or abnormal overexpression (strong and diffuse staining > 50% of tumor cells). Pathogenic variants of TP53 were identified with a targeted next generation sequencing (tNGS) panel. Wild type p53 expression was observed in 267 cases (75.4%), complete absence in twenty cases (5.7%) and the overexpression pattern in 67 cases (18.9%). tNGS identified a pathogenic TP53 mutation in 102 patients (29%). The overall accuracy of p53 IHC was 84.5% (95% CI 80.3-88.1), with a robust specificity of 92.1% (95% CI 88.0- 95.1), but a low sensitivity of 65.7% (95% CI 55.7-74.8). These results suggest that the performance of p53 IHC is insufficient as a surrogate marker for TP53 mutations in our real-world routine diagnostic workup of MBCL patients. By using p53 immunohistochemistry alone, there is a significant risk a TP53 mutation will be missed, resulting in misevaluation of a high-risk patient. Therefore, molecular analysis is recommended in all MBCL patients, especially for further development of risk-directed therapies based on TP53 mutation status.

Utilizing digital pathology and immunohistochemistry of p53 as an adjunct to molecular testing in myeloid disorders

TP53 mutation status guides early therapeutic decisions in the treatment of clonal myeloid disorders and serves as a simple means of monitoring response to treatment. We aim here to develop a standardized protocol for evaluating TP53 mutation status in myeloid disorders using immunohistochemistry assisted by digital image analysis and further compare this approach to manual interpretation alone. To accomplish this, we obtained 118 bone marrow biopsies from patients with hematologic malignancy and molecular testing for mutations associated with acute myeloid leukemia was performed. Clot or core biopsy slides were stained for p53 and digitally scanned. Overall mutation burden was assessed digitally using two different metrics to determine positivity, compared to the results of manual review, and correlated with molecular results. Using this approach, we found that digital analysis of immunohistochemistry stained slides performed worse than manual categorization alone in predicting TP53 mutation status in our cohort (PPV 91%, NPV 100% vs. PPV 100%, NPV 98%). While digital analysis reduced inter- and intraobserver variability when assessing mutation burden, there was poor correlation between the quantity and intensity of p53 staining and molecular analysis (R2 = 0.204). Therefore, digital image analysis of p53 immunohistochemistry accurately predicts TP53 mutation status as confirmed by molecular testing but does not offer a significant advantage over manual categorization alone. However, this approach offers a highly standardized methodology for monitoring disease status or response to treatment once a diagnosis has been made.