Morphology, DNA ploidy and HPV in lung cancer and head and neck cancer

YEATS domain-containing protein GAS41 regulates nuclear shape by working in concert with BRD2 and the mediator complex in colorectal cancer

The maintenance of nuclear shape is essential for cellular homeostasis and disruptions in this process have been linked to various pathological conditions, including cancer, laminopathies, and aging. Despite the significance of nuclear shape, the precise molecular mechanisms controlling it are not fully understood. In this study, we have identified the YEATS domain-containing protein 4 (GAS41) as a previously unidentified factor involved in regulating nuclear morphology. Genetic ablation of GAS41 in colorectal cancer cells resulted in significant abnormalities in nuclear shape and inhibited cancer cell proliferation both in vitro and in vivo. Restoration experiments revealed that wild-type GAS41, but not a YEATS domain mutant devoid of histone H3 lysine 27 acetylation or crotonylation (H3K27ac/cr) binding, rescued the aberrant nuclear phenotypes in GAS41-deficient cells, highlighting the importance of GAS41's binding to H3K27ac/cr in nuclear shape regulation. Further experiments showed that GAS41 interacts with H3K27ac/cr to regulate the expression of key nuclear shape regulators, including LMNB1, LMNB2, SYNE4, and LEMD2. Mechanistically, GAS41 recruited BRD2 and the Mediator complex to gene loci of these regulators, promoting their transcriptional activation. Disruption of GAS41-H3K27ac/cr binding caused BRD2, MED14 and MED23 to dissociate from gene loci, leading to nuclear shape abnormalities. Overall, our findings demonstrate that GAS41 collaborates with BRD2 and the Mediator complex to control the expression of crucial nuclear shape regulators.

Extracting interpretable features for pathologists using weakly supervised learning to predict p16 expression in oropharyngeal cancer

One drawback of existing artificial intelligence (AI)-based histopathological prediction models is the lack of interpretability. The objective of this study is to extract p16-positive oropharyngeal squamous cell carcinoma (OPSCC) features in a form that can be interpreted by pathologists using AI model. We constructed a model for predicting p16 expression using a dataset of whole-slide images from 114 OPSCC biopsy cases. We used the clustering-constrained attention-based multiple-instance learning (CLAM) model, a weakly supervised learning approach. To improve performance, we incorporated tumor annotation into the model (Annot-CLAM) and achieved the mean area under the receiver operating characteristic curve of 0.905. Utilizing the image patches on which the model focused, we examined the features of model interest via histopathologic morphological analysis and cycle-consistent adversarial network (CycleGAN) image translation. The histopathologic morphological analysis evaluated the histopathological characteristics of image patches, revealing significant differences in the numbers of nuclei, the perimeters of the nuclei, and the intercellular bridges between p16-negative and p16-positive image patches. By using the CycleGAN-converted images, we confirmed that the sizes and densities of nuclei are significantly converted. This novel approach improves interpretability in histopathological morphology-based AI models and contributes to the advancement of clinically valuable histopathological morphological features.

Classification and Treatment of Diseases in the Age of Genome Medicine Based on Pathway Pathology

The focus of pathology as a biomedical discipline is the identification of the pathomechanisms of diseases and the integration of this knowledge into routine diagnosis and classification. Standard tools are macroscopic and microscopic analysis complemented by immunohistochemistry and molecular pathology. So far, classification has been based on the paradigm of cellular pathology established by Rudolf Virchow and others more than 150 years ago, stating that diseases originate from diseased cells. This dogma is meanwhile challenged by the fact that cells can be fully reprogrammed. Many diseases are nowadays considered to originate from undifferentiated stem cells, induced into a diseased state by genetic or epigenetic alterations. In addition, the completion of the Human Genome Project, with the identification of more than 20.000 genes and a much higher number of gene variants and mutations, led to the concept that diseases are dominated by genetics/epigenetics rather than cells of origin. The axiom of cellular pathology, however, still holds true, as cells are the smallest animate units from which diseases originate. Medical doctors and researchers nowadays have to deal with a tremendous amount of data. The International Classification of Diseases will expand from 14.400 entities/codes in ICD-10 to more than 55.000 in ICD-11. In addition, large datasets generated by “genomics“, e.g., whole-genome sequencing, expression profiling or methylome analysis, are meanwhile not only applied in research but also introduced into clinical settings. It constitutes a major task to incorporate all the data into routine medical work. Pathway pathology may help solve this problem. It is based on the realization that diseases are characterized by three essential components: (i) cells of origin/cellular context and (ii) the alteration of cellular as well as (iii) molecular/signal transduction pathways. The concept is illustrated by elaborating on two key cellular pathways, i.e., the cellular senescence of normal cells and the immortality of cancer cells, and by contrasting single cell/single pathway diseases, such as mycoplasma and coughing pneumonia, with complex diseases such as cancer, with multiple cell types as well as multiple affected cellular and signaling pathways. Importantly, the concept of pathway pathology is not just intended to classify disease, but also to conceive new treatment modalities. This article is dedicated to Dr. Leonard Hayflick, who made basic discoveries in pathway pathology not only by identifying cells causing disease (Mycoplasma pneumoniae) and establishing cell strains for treating disease (WI-38 for viral vaccines), but also by first describing cellular senescence and immortality.

Mutation analysis of tumor necrosis factor alpha-induced protein 3 gene in Hodgkin lymphoma

AIMS

Survival and proliferation of Hodgkin and Reed-Sternberg (HRS) cells, the malignant cells of classical Hodgkin lymphoma (CHL), are dependent on constitutive activation of nuclear factor kB (NF-κB). A20, encoded by TNF alpha-induced protein 3 (TNFAIP₃₎, one of the inhibitors of NF-kB, was found to be inactivated by deletions and/or point mutations in CHL.

METHODS

TNFAIP₃ mutations were examined in 37 patients with CHL by using PCR and direct sequencing. In addition, protein expression of A20 was evaluated by immunohistochemistry. Epstein-Barr virus (EBV) status of HL samples was determined by EBV EBER chromogenic in situ hybridization (ISH).

RESULTS

We identified 8 mutation positive cases in a collective of 37 investigated cases (22%). Mutations were most frequent in the nodular sclerosis subtype. Our results revealed the tendency that cases harboring A20 mutations were negative for A20 staining. None of A20 mutation-positive CHL cases showed EBV infection.

CONCLUSIONS

Our study confirms the involvement of the TNFAIP₃ tumor suppressor gene in CHL. A20 may represent a suppressor of human lymphoma and provide a critical molecular link between chronic inflammation and cancer. None of A20 mutation-positive CHL cases showed EBV infection. This fact suggests complementing functions of TNFAIP₃ inactivation and EBV infection in CHL pathogenesis and may represent an interesting point of further investigations.