The Viral Origin of Human Breast Cancer: From the Mouse Mammary Tumor Virus (MMTV) to the Human Betaretrovirus (HBRV)

Predictive modeling for breast cancer classification in the context of Bangladeshi patients by use of machine learning approach with explainable AI

Breast cancer has rapidly increased in prevalence in recent years, making it one of the leading causes of mortality worldwide. Among all cancers, it is by far the most common. Diagnosing this illness manually requires significant time and expertise. Since detecting breast cancer is a time-consuming process, preventing its further spread can be aided by creating machine-based forecasts. Machine learning and Explainable AI are crucial in classification as they not only provide accurate predictions but also offer insights into how the model arrives at its decisions, aiding in the understanding and trustworthiness of the classification results. In this study, we evaluate and compare the classification accuracy, precision, recall, and F1 scores of five different machine learning methods using a primary dataset (500 patients from Dhaka Medical College Hospital). Five different supervised machine learning techniques, including decision tree, random forest, logistic regression, naive bayes, and XGBoost, have been used to achieve optimal results on our dataset. Additionally, this study applied SHAP analysis to the XGBoost model to interpret the model's predictions and understand the impact of each feature on the model's output. We compared the accuracy with which several algorithms classified the data, as well as contrasted with other literature in this field. After final evaluation, this study found that XGBoost achieved the best model accuracy, which is 97%.

B-cell small lymphocytic lymphoma in a free-ranging South American fur seal (Arctocephalus australis)

Lymphomas are malignant neoplasms of the hematopoietic system arising from lymphocytes with highly variable biologic behavior. B-cell small lymphocytic lymphoma (B-SLL) is a non-Hodgkin lymphoma infrequently described in domestic and wild animals. The present study describes a case of B-SLL in a free-ranging adult male Arctocephalus australis in Brazil. The main necropsy findings included poor body condition, generalized lymphadenomegaly, severe and diffuse splenomegaly, and multiple, white to yellow nodules in the kidneys and small intestine. Histologically, these organs were partially or totally effaced by neoplastic small lymphocytes arranged in sheets, with moderate anisocytosis and anisokaryosis and a low mitotic count. These cells diffusely immunolabeled for CD79α and CD20, and were negative for CD3. A diagnosis of multicentric B-SLL was established and to the authors' knowledge, it has not been previously described in this genus.

Global Down-regulation of Gene Expression Induced by Mouse Mammary Tumor Virus (MMTV) in Normal Mammary Epithelial Cells

Mouse mammary tumor virus (MMTV) is a betaretrovirus that causes breast cancer in mice. The mouse mammary epithelial cells are the most permissive cells for MMTV, expressing the highest levels of virus upon infection and being the ones later transformed by the virus due to repeated rounds of infection/superinfection and integration, leading eventually to mammary tumors. The aim of this study was to identify genes and molecular pathways dysregulated by MMTV expression in mammary epithelial cells. Towards this end, mRNAseq was performed on normal mouse mammary epithelial cells stably expressing MMTV, and expression of host genes was analyzed compared with cells in its absence. The identified differentially expressed genes (DEGs) were grouped on the basis of gene ontology and relevant molecular pathways. Bioinformatics analysis identified 12 hub genes, of which 4 were up-regulated (Angp2, Ccl2, Icam, and Myc) and 8 were down-regulated (Acta2, Cd34, Col1a1, Col1a2, Cxcl12, Eln, Igf1, and Itgam) upon MMTV expression. Further screening of these DEGs showed their involvement in many diseases, especially in breast cancer progression when compared with available data. Gene Set Enrichment Analysis (GSEA) identified 31 molecular pathways dysregulated upon MMTV expression, amongst which the PI3-AKT-mTOR was observed to be the central pathway down-regulated by MMTV. Many of the DEGs and 6 of the 12 hub genes identified in this study showed expression profile similar to that observed in the PyMT mouse model of breast cancer, especially during tumor progression. Interestingly, a global down-regulation of gene expression was observed, where nearly 74% of the DEGs in HC11 cells were repressed by MMTV expression, an observation similar to what was observed in the PyMT mouse model during tumor progression, from hyperplasia to adenoma to early and late carcinomas. Comparison of our results with the Wnt1 mouse model revealed further insights into how MMTV expression could lead to activation of the Wnt1 pathway independent of insertional mutagenesis. Thus, the key pathways, DEGs, and hub genes identified in this study can provide important clues to elucidate the molecular mechanisms involved in MMTV replication, escape from cellular anti-viral response, and potential to cause cell transformation. These data also validate the use of the MMTV-infected HC11 cells as an important model to study early transcriptional changes that could lead to mammary cell transformation.

Special Issue "Human Betaretrovirus and Related Diseases"

A betaretrovirus resembling mouse mammary tumor virus (MMTV) was first linked with human breast cancer over 50 years ago [...]

Life after Cleavage: The Story of a β-Retroviral (MMTV) Signal Peptide-From Murine Lymphoma to Human Breast Cancer

An increasing body of evidence in recent years supports an association of the betaretrovirus mouse mammary tumor virus (MMTV) with human breast cancer. This is an issue that still raises heated controversy. We have come to address this association using the signal peptide p14 of the MMTV envelope precursor protein as a key element of our strategy. In addition to its signal peptide function, p14 has some significant post endoplasmic reticulum (ER)-targeting characteristics: (1) it localizes to nucleoli where it binds key proteins (RPL5 and B23) involved (among other activities) in the regulation of nucleolar stress response, ribosome biogenesis and p53 stabilization; (2) p14 is a nuclear export factor; (3) it is expressed on the cell surface of infected cells, and as such, is amenable to, and successfully used, in preventive vaccination against experimental tumors that harbor MMTV; (4) the growth of such tumors is impaired in vivo using a combination of monoclonal anti-p14 antibodies or adoptive T-cell transfer treatments; (5) p14 is a phospho-protein endogenously phosphorylated by two different serine kinases. The phosphorylation status of the two sites determines whether p14 will function in an oncogenic or tumor-suppressing capacity; (6) transcriptional activation of genes (RPL5, ErbB4) correlates with the oncogenic potential of MMTV; (7) finally, polyclonal anti-p14 antibodies have been applied in immune histochemistry analyses of breast cancer cases using formalin fixed paraffin-embedded sections, supporting the associations of MMTV with the disease. Taken together, the above findings constitute a road map towards the diagnosis and possible prevention and treatment of MMTV-associated breast cancer.

The Role of a Betaretrovirus in Human Breast Cancer: Enveloping a Conundrum

Most of the evidence that a human betaretrovirus (HBRV/HMTV) highly related to mouse mammary tumour virus (MMTV) has an etiological role in breast cancer has been summarized in a recent comprehensive Special Issue of "Viruses" entitled "Human Betaretrovirus (HBRV) and Related Diseases". Shortly after publication of this special issue, a detailed analysis of aligned env sequences was published and concluded that (i) MMTV and HBRV/HMTV cannot be distinguished on the basis of aligned env sequences and (ii) more sequence data covering the full-length env or HBRV/HMTV genomes from multiple isolates is needed. Although productive infection of human cells by MMTV (and presumably HBRV/HMTV) has been shown, it is imperative that the receptor(s) enabling HBRV/HMTV to infect human cells are defined. Moreover, there is currently no compelling data for common integration sites, in contrast to MMTV induced mammary tumorigenesis in mice, suggesting that other mechanisms of tumorigenesis are associated with HBRV/HMTV infection. These issues need to be resolved before a clear link between MMTV/HBRV/HMTV and human breast cancer can be concluded.