Showing papers by "Arnold J. Levine published in 2020"

p53: 800 million years of evolution and 40 years of discovery

Abstract: The evolutionarily conserved p53 protein and its cellular pathways mediate tumour suppression through an informed, regulated and integrated set of responses to environmental perturbations resulting in either cellular death or the maintenance of cellular homeostasis. The p53 and MDM2 proteins form a central hub in this pathway that receives stressful inputs via MDM2 and respond via p53 by informing and altering a great many other pathways and functions in the cell. The MDM2-p53 hub is one of the hubs most highly connected to other signalling pathways in the cell, and this may be why TP53 is the most commonly mutated gene in human cancers. Initial or truncal TP53 gene mutations (the first mutations in a stem cell) are selected for early in cancer development inectodermal and mesodermal-derived tissue-specific stem and progenitor cells and then, following additional mutations, produce tumours from those tissue types. In endodermal-derived tissue-specific stem or progenitor cells, TP53 mutations are functionally selected as late mutations transitioning the mutated cell into a malignant tumour. The order in which oncogenes or tumour suppressor genes are functionally selected for in a stem cell impacts the timing and development of a tumour.

P53 and The Immune Response: 40 Years of Exploration—A Plan for the Future

Abstract: The p53 field was born from a marriage of the techniques of cancer virus research and immunology. Over the past 40 years, it has followed the path of cancer research. Now cancer treatments are turning to immunotherapy, and there are many hints of the role of the p53 protein in both the regulation of the innate immune system and as an antigen in adaptive immune responses. The p53 gene and protein are part of the innate immune system, and play an important role in infectious diseases, senescence, aging, and the surveillance of repetitive DNA and RNAs. The mutant form of the p53 protein in cancers elicits both a B-cell antibody response (a tumor antigen) and a CD-8 killer T-cell response (a tumor-specific transplantation antigen). The future will take the p53-immune response field of research into cancer immunotherapy, autoimmunity, inflammatory responses, neuro-degeneration, aging, and life span, and the regulation of epigenetic stability and tissue regeneration. The next 40 years will bring the p53 gene and its proteins out of a cancer focus and into an organismic and environmental focus.

Two well-differentiated pancreatic neuroendocrine tumor mouse models

Abstract: Multiple endocrine neoplasia type 1 (MEN1) is a genetic syndrome in which patients develop neuroendocrine tumors (NETs), including pancreatic neuroendocrine tumors (PanNETs). The prolonged latency of tumor development in MEN1 patients suggests a likelihood that other mutations cooperate with Men1 to induce PanNETs. We propose that Pten loss combined with Men1 loss accelerates tumorigenesis. To test this, we developed two genetically engineered mouse models (GEMMs)—MPR (Men1flox/flox Ptenflox/flox RIP-Cre) and MPM (Men1flox/flox Ptenflox/flox MIP-Cre) using the Cre-LoxP system with insulin-specific biallelic inactivation of Men1 and Pten. Cre in the MPR mouse model was driven by the transgenic rat insulin 2 promoter while in the MPM mouse model was driven by the knock-in mouse insulin 1 promoter. Both mouse models developed well-differentiated (WD) G1/G2 PanNETs at a much shorter latency than Men1 or Pten single deletion alone and exhibited histopathology of human MEN1-like tumor. The MPR model, additionally, developed pituitary neuroendocrine tumors (PitNETs) in the same mouse at a much shorter latency than Men1 or Pten single deletion alone as well. Our data also demonstrate that Pten plays a role in NE tumorigenesis in pancreas and pituitary. Treatment with the mTOR inhibitor rapamycin delayed the growth of PanNETs in both MPR and MPM mice, as well as the growth of PitNETs, resulting in prolonged survival in MPR mice. Our MPR and MPM mouse models are the first to underscore the cooperative roles of Men1 and Pten in cancer, particularly neuroendocrine cancer. The early onset of WD PanNETs mimicking the human counterpart in MPR and MPM mice at 7 weeks provides an effective platform for evaluating therapeutic opportunities for NETs through targeting the MENIN-mediated and PI3K/AKT/mTOR signaling pathways.

Identification of relevant genetic alterations in cancer using topological data analysis.

Abstract: Large-scale cancer genomic studies enable the systematic identification of mutations that lead to the genesis and progression of tumors, uncovering the underlying molecular mechanisms and potential therapies. While some such mutations are recurrently found in many tumors, many others exist solely within a few samples, precluding detection by conventional recurrence-based statistical approaches. Integrated analysis of somatic mutations and RNA expression data across 12 tumor types reveals that mutations of cancer genes are usually accompanied by substantial changes in expression. We use topological data analysis to leverage this observation and uncover 38 elusive candidate cancer-associated genes, including inactivating mutations of the metalloproteinase ADAMTS12 in lung adenocarcinoma. We show that ADAMTS12-/- mice have a five-fold increase in the susceptibility to develop lung tumors, confirming the role of ADAMTS12 as a tumor suppressor gene. Our results demonstrate that data integration through topological techniques can increase our ability to identify previously unreported cancer-related alterations.

Mdm2: Open questions.

Abstract: The Mdm2 oncoprotein and its association with p53 were discovered 30 years ago, and a cornucopia of activities and regulatory pathways have been associated with it. In this review, we will raise questions about Mdm2 and its cousin Mdm4 that we consider worth pursuing in future research, reaching from molecular structures and intracellular activities all the way to development, evolution, and cancer therapy. We anticipate that such research will not only close a few gaps in our knowledge but could add new dimensions to our current view. This compilation of questions contributes to the preparation for the 10th Mdm2 Workshop in Tokyo.

Functional network analysis reveals an immune tolerance mechanism in cancer.

Abstract: We present a technique to construct a simplification of a feature network which can be used for interactive data exploration, biological hypothesis generation, and the detection of communities or modules of cofunctional features. These are modules of features that are not necessarily correlated, but nevertheless exhibit common function in their network context as measured by similarity of relationships with neighboring features. In the case of genetic networks, traditional pathway analyses tend to assume that, ideally, all genes in a module exhibit very similar function, independent of relationships with other genes. The proposed technique explicitly relaxes this assumption by employing the comparison of relational profiles. For example, two genes which always activate a third gene are grouped together even if they never do so concurrently. They have common, but not identical, function. The comparison is driven by an average of a certain computationally efficient comparison metric between Gaussian mixture models. The method has its basis in the local connection structure of the network and the collection of joint distributions of the data associated with nodal neighborhoods. It is benchmarked on networks with known community structures. As the main application, we analyzed the gene regulatory network in lung adenocarcinoma, finding a cofunctional module of genes including the pregnancy-specific glycoproteins (PSGs). About 20% of patients with lung, breast, uterus, and colon cancer in The Cancer Genome Atlas (TCGA) have an elevated PSG+ signature, with associated poor group prognosis. In conjunction with previous results relating PSGs to tolerance in the immune system, these findings implicate the PSGs in a potential immune tolerance mechanism of cancers.

Identification of Relevant Genetic Alterations in Cancer using Topological Data Analysis

Abstract: Large-scale cancer genomic studies enable the systematic identification of mutations that lead to the genesis and progression of tumors, uncovering the underlying molecular mechanisms and potential therapies. While some such mutations are recurrently found in many tumors, many others exist solely within a few samples, precluding detection by conventional recurrence-based statistical approaches. Integrated analysis of somatic mutations and RNA expression data across 12 tumor types reveals that mutations of cancer genes are usually accompanied by substantial changes in expression. We use topological data analysis to leverage this observation and uncover 38 elusive candidate cancer-associated genes, including inactivating mutations of the metalloproteinase ADAMTS12 in lung adenocarcinoma. We show that ADAMTS12−/− mice have a five-fold increase in the susceptibility to develop lung tumors, confirming the role of ADAMTS12 as a tumor suppressor gene. Our results demonstrate that data integration through topological techniques can increase our ability to identify previously unreported cancer-related alterations.

Non-Random Selection of Cancer-Causing Mutations in Tissue-Specific Stem Cells Cause Cancer.

Abstract: Tissue-specific stem cells are the target for selected mutations in oncogenes or tumor suppressor genes that enhance the fitness of these cells, resulting in a self-limited clonal expansion and eventual cancer development. The initial or truncal mutations in the stem cell select for subsequent mutations that enhance their fitness, producing a reproducible order of mutations, selected for in each tissue type, during cancer development. Mutations in stem cells occur randomly, but the selection for increased fitness, occurs non-randomly, conferring a functional order on the selection of mutations. Tissue-specific stem cells are "units of natural selection" for somatic stem cells throughout life. This is why inherited cancer-causing mutations, which, by definition, are initial or truncal mutations, are observed to cause cancers with limited tissue specificities, even though the mutations are present in stem cells for all tissue types. In future studies, we need to understand why the same signal transduction pathways function differently in different tissue-specific stem cells. We also need to understand the truncal mutations for each cancer type, so as to eradicate the stem cell clones for that cancer before they produce a malignant tumor. To accomplish these objectives, we need to carry out new kinds of clinical trials with drugs that target mutations in tissue-specific stem cells.