Detection of gene mutations in gastric cancer tissues using a commercial sequencing panel

Cross-Talk between p53 and Wnt Signaling in Cancer

Targeting cancer hallmarks is a cardinal strategy to improve antineoplastic treatment. However, cross-talk between signaling pathways and key oncogenic processes frequently convey resistance to targeted therapies. The p53 and Wnt pathway play vital roles for the biology of many tumors, as they are critically involved in cancer onset and progression. Over recent decades, a high level of interaction between the two pathways has been revealed. Here, we provide a comprehensive overview of molecular interactions between the p53 and Wnt pathway discovered in cancer, including complex feedback loops and reciprocal transactivation. The mutational landscape of genes associated with p53 and Wnt signaling is described, including mutual exclusive and co-occurring genetic alterations. Finally, we summarize the functional consequences of this cross-talk for cancer phenotypes, such as invasiveness, metastasis or drug resistance, and discuss potential strategies to pharmacologically target the p53-Wnt interaction.

Multicellular Modelling of Difficult-to-Treat Gastrointestinal Cancers: Current Possibilities and Challenges

Cancers affecting the gastrointestinal system are highly prevalent and their incidence is still increasing. Among them, gastric and pancreatic cancers have a dismal prognosis (survival of 5–20%) and are defined as difficult-to-treat cancers. This reflects the urge for novel therapeutic targets and aims for personalised therapies. As a prerequisite for identifying targets and test therapeutic interventions, the development of well-established, translational and reliable preclinical research models is instrumental. This review discusses the development, advantages and limitations of both patient-derived organoids (PDO) and patient-derived xenografts (PDX) for gastric and pancreatic ductal adenocarcinoma (PDAC). First and next generation multicellular PDO/PDX models are believed to faithfully generate a patient-specific avatar in a preclinical setting, opening novel therapeutic directions for these difficult-to-treat cancers. Excitingly, future opportunities such as PDO co-cultures with immune or stromal cells, organoid-on-a-chip models and humanised PDXs are the basis of a completely new area, offering close-to-human models. These tools can be exploited to understand cancer heterogeneity, which is indispensable to pave the way towards more tumour-specific therapies and, with that, better survival for patients.

Prediction of genetic alterations from gastric cancer histopathology images using a fully automated deep learning approach

BACKGROUND

Studies correlating specific genetic mutations and treatment response are ongoing to establish an effective treatment strategy for gastric cancer (GC). To facilitate this research, a cost- and time-effective method to analyze the mutational status is necessary. Deep learning (DL) has been successfully applied to analyze hematoxylin and eosin (H and E)-stained tissue slide images.

AIM

To test the feasibility of DL-based classifiers for the frequently occurring mutations from the H and E-stained GC tissue whole slide images (WSIs).

METHODS

From the GC dataset of The Cancer Genome Atlas (TCGA-STAD), wild-type/mutation classifiers for CDH1, ERBB2, KRAS, PIK3CA, and TP53 genes were trained on 360 × 360-pixel patches of tissue images.

RESULTS

The area under the curve (AUC) for the receiver operating characteristic (ROC) curves ranged from 0.727 to 0.862 for the TCGA frozen WSIs and 0.661 to 0.858 for the TCGA formalin-fixed paraffin-embedded (FFPE) WSIs. The performance of the classifier can be improved by adding new FFPE WSI training dataset from our institute. The classifiers trained for mutation prediction in colorectal cancer completely failed to predict the mutational status in GC, indicating that DL-based mutation classifiers are incompatible between different cancers.

CONCLUSION

This study concluded that DL could predict genetic mutations in H and E-stained tissue slides when they are trained with appropriate tissue data.

Cervical carcinomas with serous-like papillary and micropapillary components: illustrating the heterogeneity of primary cervical carcinomas

Recent changes in the classification of cervical adenocarcinomas have re-categorized serous carcinoma as potentially nonexistent. However, clinical and pathological profiles of cervical adenocarcinomas with serous-like morphological features have not been systematically evaluated using the latest taxonomy and biomarkers. We studied 14 cases of primary cervical carcinomas with serous-like morphologies (papillary and micropapillary patterns). None of these cases exhibited evidence of serous carcinoma involving the upper tracts. Patient ages ranged between 34 and 86 years, most presented with abnormal uterine bleeding. Histologically, ten cases were classified as human papillomavirus (HPV)-associated carcinomas (eight usual-type endocervical adenocarcinomas and two adenosquamous carcinomas), of which six exhibited a papillary pattern and four had a micropapillary pattern. The four remaining cases were HPV-independent gastric-type adenocarcinomas, which displayed a papillary pattern in one case and a micropapillary pattern in three others. All ten HPV-associated carcinomas displayed block positive p16 and wild-type p53 by immunohistochemistry, with nine of them confirmed by HPV testing. Two of the four gastric-type adenocarcinomas had mutation-type p53, one of which also being p16 block positive. HER2 overexpression was demonstrated in 3/14 (21.4%) cases (2 HPV-associated and 1 HPV-independent). PD-L1 expression was identified in 4/10 (40%) cases, all HPV-associated. Targeted next-generation sequencing was performed in two cases with a micropapillary pattern, revealing a missense variant in ATM in an HPV-associated tumor and missense variants in TP53 and SMARCB1 in an HPV-independent tumor. The results demonstrated that primary endocervical adenocarcinomas can mimic the appearance of serous carcinoma, while not representing serous carcinoma. Serous-like papillary and micropapillary patterns may be present in both HPV-associated and HPV-independent cervical carcinomas, but none of the cases studied were unequivocally serous upon detailed analysis. Our findings support the exclusion of "cervical serous carcinoma" from existing classifications of cervical adenocarcinoma.

Identification of Recurrent TERT Promoter Mutations in Intrathyroid Thymic Carcinomas

Intrathyroid thymic carcinoma (ITTC) is a rare malignant neoplasm considered to be a eutopic thymic carcinoma (TC) arising ectopically in the thyroid. Histopathologically, ITTC resembles squamous cell carcinoma of the thymus with positive TC markers such as CD5 and c-KIT. Despite these similar histological findings, ITTC is clinically less aggressive than TC. In this study, we compared clinical, histological, and genetic characteristics of ITTCs and TCs. We collected 9 ITTCs and 8 TCs with their clinicopathological profiles. Immunohistochemistry for CD5, p63, CD117/c-KIT, Ki-67, p53, TTF-1, thyroglobulin, PAX8, EGFR, and PD-L1/CD274 plus in situ hybridization for EBER was performed. We further investigated mutation status of KIT, EGFR, BRAF, and TERT promoter using Sanger sequencing. In our study, ITTCs affected significantly younger patients than TCs. After a mean follow-up of 86 months, all patients with ITTC were alive, while two patients with TC had died. Immunohistochemistry showed ITTCs and TCs had a similar immunophenotype except for EGFR and p53. Genetic analysis did not identify KIT or BRAF mutations in any ITTCs or TCs. EGFR mutations were positive in 11% (1/9) of ITTCs and 25% (2/8) of TCs. Notably, TERT promoter C228T mutation was identified in 22% (2/9) of ITTCs but none of the TCs. There were no significant differences in age, tumor size, or sex between TERT-mutated and TERT-wild-type ITTCs. Collectively, ITTC and TC have similar histopathologic and immunophenotypic features but different clinical outcomes. Recurrent TERT promoter mutation may be a key event related to cancer progression in ITTCs and warrants further investigation.