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Stephen B Baylin is a codirector of the Cancer Biology Program at The Sidney Kimmel Comprehensive Cancer Center at Johns Hopkins and the Virginia and DK Ludwig Professor of Oncology and Medicine. Baylin attended Duke University, where he earned his medical degree and completed his internship and first year residency in internal medicine. He then worked for 2 years at the National Heart and Lung Institute of the NIH. In 1971, he joined the departments of oncology and medicine at Johns Hopkins University School of Medicine. His research interests include cellular biology and genetics of cancer, specifically epigenetics or genetic modifications other than those in DNA that can affect cell behavior, and silencing of tumor suppressor genes and tumor progression. His research has looked at the mechanisms through which variations in tumor cells derive, and cell differentiation in cancers such as medullary thyroid carcinoma and small-cell lung carcinoma. He has served on the American Association for Cancer Research Board of Directors, and is an associate editor of Cancer Research. He has also presented frequently at AACR conferences and chaired the special conference on ‘DNA Methylation, Imprinting and the Epigenetics of Cancer’. He has authored or coauthored more than 370 publications.

The past decade has witnessed a rapid progress in our understanding of the genetics of cancer and its progression. Probabilistic and statistical modeling played a pivotal role in the discovery of general patterns from cancer genomics datasets and continue to be of central importance for personalized medicine. Scientists have programmed the living organisms using these circuits to attain multiple, delicate and well-defined functions. With the integration of tools or technologies from other disciplines, these rewired cells can achieve even more complex tasks. In this review we introduce cancer genomics from a probabilistic and statistical perspective. We start from (1) functional classification of genes into oncogenes and tumor suppressor genes, then (2) demonstrate the importance of comprehensive analysis of different mutation types for individual cancer genomes, followed by (3) tumor purity analysis, which in turn leads to (4) the concept of ploidy and clonality, that is next connected to (5) tumor evolution under treatment pressure, which yields insights into cancer drug resistance. We also discuss future challenges including the non-coding genomic regions, integrative analysis of genomics and epigenomics, as well as early cancer detection. We believe probabilistic and statistical modeling will continue to play important roles for novel discoveries in the field of cancer genomics and personalized medicine.

Cancer resistance varies amongst individuals, although its host genetic underpinnings remain largely elusive. Remissions of sarcomas were first reported following repeated injections of patients with mixtures of killed bacteria—Coley’s toxins—a phenomenon, which was subsequently causally traced to induction of innate immunity. Here we reveal remission ofDrosophilaepithelial neoplasms by genetically triggered host innate immunity via Toll signaling. These neoplasms display capacities to receive and, in rare instances, induce Toll signaling. A tumor-induced and progressive Toll signaling, however, did not culminate in tumor suppression. By contrast,Drosophilahosts heterozygous forspn27A1mutation, which constitutively produce activated Toll ligand, SpzAct, displayed comprehensive tumor remission via Toll-induced, NF-κB-mediated, tumor cell death. Our results reveal a novel node of host genetic cancer resistance via serpin-dependent Toll signaling.

Genetics of cancer is a hot topic, an excellent example of translational medicine. Risk stratification, selection of cases for surgery in Bethesda categories 3 &4 FNAB are examples of the high impact of genetic evaluation in thyroid neoplasia.

Significant strides have been made in our understanding of the genetics of cancer, beginning with the initial identification of oncogenes and tumor suppressor genes and culminating in the genomic profiling of tumors being routinely available in clinical practice. This progress has also led to some remarkable successes in molecularly targeted therapy, with the development of agents that target genetically driven tumor dependencies and vulnerabilities. This chapter will discuss the broad principles underlying targeted therapy and the difficulties that have been encountered, using illustrative examples from a range of cancer types.

The Sleeping Beauty (SB) transposon insertional mutagenesis system offers a streamlined approach to identify genetic drivers of cancer. With a relatively random insertion profile, SB is uniquely positioned for conducting unbiased forward genetic screens. Indeed, SB mouse models of cancer have revealed insights into the genetics of tumorigenesis. In this review, we highlight experiments that have exploited the SB system to interrogate the genetics of cancer in distinct biological contexts. We also propose experimental designs that could further our understanding of the relationship between tumor microenvironment and tumor progression.

Despite considerable progress in understanding the biology and genetics of cancer progression, the development of effective therapies against cancer need physiological and predictive preclinical models. In this context, patient-derived xenograft (PDX) models has become a standard tool as they reproduce accurately the behavior of tumor of origin, in term of histological and molecular phenotype and response to chemotherapy. Although PDXs in vivo models are indispensable for preclinical studies, they suffer from some limitations due to study costs related to tumor maintenance on mice, variable engraftment rate, growth delay and limited throughput for large-scale drug screening. To address this problem and propose a time a cost effective preclinical screening tool, we developed a panel of PDX-derived low-passage 2D cell lines as a convenient in vitro pre-screening platform to profile compound activity. Different PDX models including breast, lung, colon, melanoma, glioblastoma and hepatoblastoma were tested for their capacity to generate cell lines maintaining the characteristics of the parental PDX tumor and usable for in vitro assays. Today, we succeeded with a series of 50 PDX models with 83% success rate. Tumor cells isolated from PDX tumor tissue were cultured under different media and matrix conditions, allowing at least 5 passages in culture. A Short Tandem Repeat (STR) comparison profile was done with the parental PDX before performing a master bank. We performed short term 2D cytotoxicity assays and long term colony assays to compare cell lines in vitro drug sensitivity with their parental PDX in vivo drug response and overall, the results show that this panel reproduced the drug response profile of the original PDXs with chemotherapies, PARP inhibitors, an ADC (T-DM1) and FGFR-targeting therapies. Moreover, cellular models engrafted back onto mice showed in vivo response to chemotherapies similar to that of the parental PDX confirming the identical behavior of cell line/PDX couples. As the use of cellular models is still considered as a standard for early preclinical test to evaluate drug response before moving to in vivo assays, our PDX-derived cell line platform appeared to be a robust and relevant tool. Furthermore, since the main concern when using in vitro models is the representativeness of the results obtained when transposed to in vivo models, the similarities between cell lines and parental PDX should maximize success of further in vivo preclinical drug development. Citation Format: Olivier Deas, Sophie Banis, Kathleen Flosseau, Lea Sinayen, Enora Le Ven, Jean-Gabriel Judde, Stefano Cairo. A preclinical platform of PDX-derived cell lines as a tool for pharmacological screening and functional studies [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2021; 2021 Apr 10-15 and May 17-21. Philadelphia (PA): AACR; Cancer Res 2021;81(13_Suppl):Abstract nr 3014.

Dr David Adams speaks to Editor of Oncology Central, Jade Parker: Based at Wellcome Trust Sanger Institute as a senior group leader, David Adams uses DNA sequencing of patients and genetic screens in human cells and mice to identify cancer genes and genetic interactions. The Adams group studies the mechanisms of cancer development, particularly skin cancer (melanoma) and colorectal cancer. They sequence DNA from families with a high incidence of cancer and also tumors from patients to understand why some people are at greater risk of tumor development and how cancers evolve. The group also performs functional studies in cultured cells and in mice to understand how factors such as DNA mutations and the immune system influence tumor growth.

An overview of the multiple genetic and and environmental factors which contribute to the aetiology of malignancy.

The exact cause of cancer is one of the most immutable medical questions of the century. Cancer as an evolutionary disease must have a purpose and understanding the purpose is more important than decoding the cause. The model of cancer proposed herein, provides a link between the cellular biochemistry and cellular genetics of cancer evolution. We thus call this model as the “Nexus model” of cancer. The Nexus model is an effort to identify the most apparent route to the disease. We have tried to utilize existing cancer literature to identify the most plausible causes of cellular transition in cancer, where the primary cancer-causing agents (physical, chemical or biological) act as inducing factors to produce cellular impeders. These cellular impeders are further linked to the Nexus. The Nexus then generates codes for epigenetics and genetics in cancer development.

Supplemental Digital Content is available in the text., Background: Cancer therapy–induced cardiomyopathy (CCM) is associated with cumulative drug exposures and preexisting cardiovascular disorders. These parameters incompletely account for substantial interindividual susceptibility to CCM. We hypothesized that rare variants in cardiomyopathy genes contribute to CCM. Methods: We studied 213 patients with CCM from 3 cohorts: retrospectively recruited adults with diverse cancers (n=99), prospectively phenotyped adults with breast cancer (n=73), and prospectively phenotyped children with acute myeloid leukemia (n=41). Cardiomyopathy genes, including 9 prespecified genes, were sequenced. The prevalence of rare variants was compared between CCM cohorts and The Cancer Genome Atlas participants (n=2053), healthy volunteers (n=445), and an ancestry-matched reference population. Clinical characteristics and outcomes were assessed and stratified by genotypes. A prevalent CCM genotype was modeled in anthracycline-treated mice. Results: CCM was diagnosed 0.4 to 9 years after chemotherapy; 90% of these patients received anthracyclines. Adult patients with CCM had cardiovascular risk factors similar to the US population. Among 9 prioritized genes, patients with CCM had more rare protein-altering variants than comparative cohorts (P≤1.98e–04). Titin-truncating variants (TTNtvs) predominated, occurring in 7.5% of patients with CCM versus 1.1% of The Cancer Genome Atlas participants (P=7.36e–08), 0.7% of healthy volunteers (P=3.42e–06), and 0.6% of the reference population (P=5.87e–14). Adult patients who had CCM with TTNtvs experienced more heart failure and atrial fibrillation (P=0.003) and impaired myocardial recovery (P=0.03) than those without. Consistent with human data, anthracycline-treated TTNtv mice and isolated TTNtv cardiomyocytes showed sustained contractile dysfunction unlike wild-type (P=0.0004 and P

Elizabeth McNally, MD, PhD, has spent three decades studying the genetics of heart and muscle disease. Her work has yielded new insights into the development and presentation of cardiomyopathy and muscular dystrophy. Dr McNally’s interests are rooted in her days as an undergraduate student at Barnard College. She earned her medical degree and doctorate in microbiology and immunology from Albert Einstein College of Medicine. She did her internship, residency and cardiovascular fellowship at Brigham and Women’s Hospital, and genetics fellowship at Boston Children’s Hospital. Before joining Northwestern University last year, Dr McNally, a Chicago native, had been at the University of Chicago since 1996. Among her nearly 200 publications are studies on developing genetic profiling to identify mutations underlying cardiomyopathy, including a collaborative project associating a single mutation with a range of outcomes,1 and research demonstrating the utility of whole-genome sequencing to find individual mutations in cardiomyopathy patients,2 and of a supercomputer to facilitate whole-genome analysis.3 She has explored how molecular modifiers—focusing on the TGF-beta pathway—change disease outcomes, both in animal models4–6 of muscular dystrophy and cardiomyopathy, and in patients7 with Duchenne muscular dystrophy. Recent work has proposed a novel approach8 to modulating this pathway. Other studies have identified a new modifier pathway mediating cell repair in striated muscle9 and elucidated the role of KATP channels in the neonatal heart’s shift to adult metabolism.10 In September, McNally became director of Northwestern’s Center for Genetic Medicine, with the goal of transforming how genetic information is used clinically. She plans to capitalize on advances in genetic sequencing, leverage the high heritability of cardiovascular and neurological disease, and navigate the dynamic genetics of cancer, to improve patient outcomes. I lived in the northwest suburbs of Chicago and really was not raised in a …

Cancer of unknown primary site (CUP) is a fatal cancer diagnosed through metastases at various organs. Little is known about germline genetics of CUP which appears worth of a search in view of reported familial associations in CUP. In the present study, samples from CUP patients were identified from 2 Swedish biobanks and a German clinical trial, totaling 578 CUP patients and 7628 regionally matched controls. Diagnostic data specified the organ where metastases were diagnosed. We carried out a genome-wide association study on CUP cases and controls. In the whole sample set, 6 loci reached an allelic p-value in the range of 10-7 and were supported by data from the three centers. Three associations were located next to non-coding RNA genes. rs2660852 flanked 5'UTR of LTA4H (leukotriene A4 hydrolase), rs477145 was intronic to TIAM1 (T-cell lymphoma invasion and metastases) and rs2835931 was intronic to KCNJ6 (potassium channel, inwardly rectifying subfamily J, member 6). In analysis of subgroups of CUP patients (smokers, non-smokers and CUP with liver metastases) genome-wide significant associations were noted. For patients with liver metastases associations on chromosome 6 and 11, the latter including a cluster of genes DHCR7 and NADSYN1, encoding key enzymes in cholesterol and NAD synthesis, and KRTAP5-7, encoding a keratin associated protein. This first GWAS on CUP provide preliminary evidence that germline genes relating to inflammation (LTA4H), metastatic promotion (TIAM1) in association with lipid metabolic disturbance (chromosome 11 cluster) may contribute to the risk of CUP.

In recent years, partly due to aging populations and partly due to worsening environmental factors, the frequency of cancer has increased significantly. Fortunately, thanks to the modern technological revolution, the end of the twentieth and the first years of the twenty-first centuries witnessed a progress of epical proportions in the molecular biology, immunology and genetics of cancer. This progress was reflected as remarkable advances in diagnosis and treatment of cancer. Yet the definition of “cancer” remained the same for centuries.

The first joint meeting of the International Society for Cellular Oncology (ISCO) and the European Workshop on Cytogenetics and Molecular Genetics of Solid Tumors (EWCMST), organized by Bauke Ylstra, Juan Cigudosa and Nick Gilbert, was held from 4 to 8 March, 2012 in Palma de Mallorca, Spain. This meeting provided a novel and unique opportunity to jointly present the latest updates on the genetics of cancer and its implications for diagnosis, prognosis and therapy, now and in the future. Various aspects were highlighted, including the identification of effective therapeutic targets, the role of cellular senescence in tumor development and therapy, chromosome translocations in leukemias and solid tumors, mechanisms underlying fragile sites and chromosome instability, tumor-associated ‘omics’ landscapes, genetic and epidemiologic risk factors, the role of tissue and cancer stem cells, angiogenesis and the tumor micro-environment, and the epigenetics of cancer. In this report, new insights and clinical advancements related to these various topics are provided, based on information presented at the meeting.

Human colorectal cancer (CRC) is one of the better-understood systems for studying the genetics of cancer initiation and progression. To develop a cross-species comparison strategy for identifying CRC causative gene or genomic alterations, we performed array comparative genomic hybridization (aCGH) to investigate copy number abnormalities (CNAs), one of the most prominent lesion types reported for human CRCs, in 10 spontaneously occurring canine CRCs. The results revealed for the first time a strong degree of genetic homology between sporadic canine and human CRCs. First, we saw that between 5% and 22% of the canine genome was amplified/deleted in these tumors, and that, reminiscent of human CRCs, the total altered sequences directly correlated to the tumor's progression stage, origin, and likely microsatellite instability status. Second, when mapping the identified CNAs onto syntenic regions of the human genome, we noted that the canine orthologs of genes participating in known human CRC pathways were recurrently disrupted, indicating that these pathways might be altered in the canine CRCs as well. Last, we observed a significant overlapping of CNAs between human and canine tumors, and tumors from the two species were clustered according to the tumor subtypes but not the species. Significantly, compared with the shared CNAs, we found that species-specific (especially human-specific) CNAs localize to evolutionarily unstable regions that harbor more segmental duplications and interspecies genomic rearrangement breakpoints. These findings indicate that CNAs recurrent between human and dog CRCs may have a higher probability of being cancer-causative, compared with CNAs found in one species only.

Three years ago, when the National Cancer Institute proposed its monumental $1.5 billion effort to catalog the genomic changes involved in cancer, the goal was to improve the ability to diagnose, treat, and prevent cancer. Now the first results of The Cancer Genome Atlas project (TCGA) have arrived, and they reinforce the emerging realization that the more researchers investigate the genetics of cancer, the farther away new therapeutic applications seem to get. In response, some researchers say that it's time to step back and look at cancer holistically, searching not for the individual genetic mutations but instead for unifying principles that underlie the disease process. “This idea of digging deep into the genome gives you a lot of information, and it's an important tool, but it's really only one tool,” said Lynn Hlatky, Ph.D., director of the Center of Cancer Systems Biology at Tufts University in Boston. “If your goal is making progress therapeutically, I think it's not the best investment to dig this deep until you have a larger overriding principle that really works for you. You need unifying principles that are predictive.” TCGA was intended to catalog all the genetic alterations involved in cancer and provide a roadmap for understanding how cancer develops and spreads. But the genetic complexity of cancer is making it more difficult to sort out which genetic changes actually cause disease. The NCI's $100 million pilot project—examining genetic changes in glioblastoma multiforme, the most common adult brain cancer—revealed a genetic train wreck of gross genomic alterations and mutations and signaling gone awry. But perhaps most surprisingly, the brain tumor study, which appeared in the journals Science and Nature in the first week of September, revealed new mutations associated with chemotherapeutic treatment for glioblastoma multiforme. The finding reveals that the array of mutations shifts with treatment, making genetic characterization a moving target. Parallel studies still under way that are looking at genetic changes in ovarian and lung cancers, have not yet been published. In the brain cancer project, the investigators studied 206 previously collected primary tumor samples, including 21 samples collected after treatment. Of these, the investigators selected 91 tumor samples for mutation analysis in 601 genes known to be important in cancer. They found 453 mutations in 223 genes, one-third of which had multiple mutations. Moreover, the tumors had an array of genetic differences among them, with most mutations occurring in only a few cases. Lynda Chin, M.D., the co-principal investigator of TCGA's center at Harvard Medical School, acknowledges the challenges of evaluating so many data but says that newly developed computational tools are proving that finding potentially clinically relevant information is possible. “Among the complexity of the genome, the question is: can we identify things that are of value, that are not just noise?” she said. “I think the answer is yes. I think the data now show, even with today's technology, we are able to detect these biologically important events, and they are already changing the way we think about cancer.” Chin, scientific director of the Belfer Cancer Genomics Center at Dana-Farber Cancer Institute, points to the unexpected revelation, described in TCGA research network's Sept. 4, 2008, Nature article, that tumors from patients with recurrent glioblastoma multiforme develop genetic resistance to temozolomide, a common chemotherapy treatment for treating the disease. Genomic analysis of recurrent glioblastoma multiforme revealed that patients had developed a secondary mutation in a key DNA mismatch repair gene that allowed the tumor cells to evade the killing action of temozolomide. That information, she said, will allow researchers to test whether calcium channel blockers, a class of compounds recently found to inhibit the growth cells with mismatch repair defects, could prevent the emergence of drug resistance. The research also reveals a pattern of gene mutations in a network of biochemical pathways, some of which were known to be involved in glioblastoma development, but with new insight into mutations in genes, such as PIK3R1, that were not previously known to be important in the disease. Before this study, scientists had identified mutations in the catalytic domain, p110a, which help drive tumor growth. Now investigators are reporting new mutations that probably interfere with the regulatory region of PI3K, a popular target for drug companies that are developing new cancer treatments. “There are at least 10 drug companies developing inhibitors to PI3 kinase, and they all want to know how to pick patients who will respond,” said Chin. “They say, ‘Perhaps it should be patients with mutations in the catalytic domain?’ But now we know the cancer can activate the enzyme by mutating not only the catalytic domain, the p110a, but also the regulatory domain.” The finding adds another level of complexity to the effort to predict who will respond to PI3K inhibitors, she said. It suggests that looking at mutations in the catalytic domain are not enough. Some cancers appear to find other ways to activate this crucial growth pathway. The complexity of the problem is discouraging to those investigators looking to find the next targeted therapy for cancer. Right now, “we need 20 different drugs against 20 different targets,” said Chin. “We need to get to that point of having a collection of effective drugs and knowing when to use which combination based on a genetic profile of each patient. Obviously, we are not there yet.”

Constitutional (hereditary) genetic variation and somatic genetic alterations acquired during transformation to the neoplastic phenotype are both critical determinants of cancer outcome, and can ultimately have a significant effect on cancer survivorship. This article discusses the role of constitutional and somatic genetics in determining outcome and survivorship following a diagnosis of cancer using illustrative examples primarily from the hematologic malignancies.

An evolutionary perspective can help unify disparate observations and make testable predictions. We consider an evolutionary model in relation to two mechanistic frameworks of cancer biology: multistage carcinogenesis and the hallmarks of cancer. The multistage model predicts that cancer risk increases with body size and longevity; however, this is not observed across species (Peto's paradox), but the paradox is resolved by invoking the evolution of additional genetic mechanisms to suppress cancer in large, long-lived species. It is when cancer cells overcome these defence mechanisms that they exhibit the hallmarks of cancer, driving the ongoing evolution of these defences, which in turn is expected to create the differences observed in the genetics of cancer across species and tissues. To illustrate the utility of an evolutionary model we examined some recently published data linking stem-cell divisions and cancer incidence across a range of tissues and show why the original analysis was faulty, and demonstrate that the data are consistent with a multistage model varying from three to seven mutational hits across different tissues. Finally, we demonstrate how an evolutionary model can both define patterns of inherited (familial) cancer and explain the prevalence of cancer in post-reproductive years, including the dominance of epithelial cancers.

Cancer affects approximately 1 in 3 individuals. An individual's susceptibility to cancer is partly determined by environmental exposures and by the combination of inherited cancer susceptibility and resistance genes. Initial mapping of these low penetrance cancer susceptibility genes has been done in the mouse because human low penetrance genes are extremely difficult to find using traditional methods due to heterogeneity and interacting factors. Also, the choice of candidate genes for human association studies can miss the unknown or unexpected. Mouse models also have limitations; it can be difficult to identify causal polymorphisms in the mouse because linkage disequilibrium often extends across several genes. To exploit the strengths of both systems, we outline a cross-species strategy to identify human variants associated with increased cancer risk. This approach uses linkage analysis and haplotyping, allelic imbalance in tumors, and gene expression studies in the mouse, combined with association studies and tumor imbalance studies in humans to identify causal cancer susceptibility variants. Allelic variants in both mouse and human can then be used to better understand the mechanisms behind cancer risk and as targets for intervention.

The last few decades have seen tremendous advances in the understanding of human genetics, especially since the sequencing of the human genome in 2003. With rectal cancer, as with all cancers, genetics is at the center of its etiology, whether it is associated with an inherited syndrome or a somatic mutation from environmental or other oncogenic factors. Understanding the genetics of cancer has improved the understanding of all aspects of oncology and cancer biology, such as cancer progression and spread, cancer prevention, and cancer treatment, especially considering “personalized medicine” that allows an individual’s cancer “genetic signature” to be used to tailor therapy. Unlike the surgical treatment of rectal cancer addressed in this textbook, there is little unique to rectal cancer relative to colon cancer when discussing cancer genetics and cancer biology. Instead, most of the research and advances in this field have focused on both colon and rectal cancer (CRC) based on their indistinguishable genetic signature [1], and therefore this chapter will focus on the genetics of CRC with particular attention to the impact of genetics on cancer development as well as cancer outcomes and chemotherapeutic treatment. Additionally, CRC screening and chemoprevention options, critical for early detection and prevention efforts and also not often specific to rectal cancer, will be addressed.

Improvements in cancer care have historically been predicated on significant scientific and technological advances, such as antisepsis in surgery, and the discovery of the therapeutic benefits of radiation and chemotherapeutic drugs. The past 30 years have seen an exponential increase in our knowledge of the biology and genetics of cancer, built on a massive and sustained research effort worldwide. Yet over the same period, significant changes in cancer outcomes have occurred largely as a result of public health measures and through incremental advances in existing technologies. The present paper examines the extent to which the new knowledge of cancer genetics has impacted on current patient care. It considers some of the issues that may have served to lessen this impact, as well as some of the reasons for this apparent imbalance between action and outcome.

Metastasis is the most lethal attribute of a cancer. There is a critical need for markers that will accurately distinguish those histologic lesions and disseminated cells that have a high probability of causing clinically important metastatic disease from those cells that will remain indolent. Despite the explosion in new information regarding the genetics of cancer, only six human genes have thus far been shown to functionally suppress metastasis. The present review and perspective describes the evolving view of the mechanisms that regulate metastasis, and the importance of metastasis-suppressor genes in this process. Specifically, the clinical problem of metastatic prostate cancer, the identification of metastatic colonization as a therapeutic target, and the identification and functional characterization of prostate cancer metastasis-suppressor genes are discussed.

Background The etiology of cancer involves a complex series of genetic and environmental conditions. To better represent and study the intricate genetics of cancer onset and progression, we construct a network of biological interactions to search for groups of genes that compose cancer-related modules. Three cancer expression datasets are investigated to prioritize genes and interactions associated with cancer outcomes. Using a graph-based approach to search for communities of phenotype-related genes in microarray data, we find modules of genes associated with cancer phenotypes in a weighted interaction network. Results We implement Walktrap, a random-walk-based community detection algorithm, to identify biological modules predisposing to tumor growth in 22 hepatocellular carcinoma samples (GSE14520), adenoma development in 32 colorectal cancer samples (GSE8671), and prognosis in 198 breast cancer patients (GSE7390). For each study, we find the best scoring partitions under a maximum cluster size of 200 nodes. Significant modules highlight groups of genes that are functionally related to cancer and show promise as therapeutic targets; these include interactions among transcription factors (SPIB, RPS6KA2 and RPS6KA6), cell-cycle regulatory genes (BRSK1, WEE1 and CDC25C), modulators of the cell-cycle and proliferation (CBLC and IRS2) and genes that regulate and participate in the map-kinase pathway (MAPK9, DUSP1, DUSP9, RIPK2). To assess the performance of Walktrap to find genomic modules (Walktrap-GM), we evaluate our results against other tools recently developed to discover disease modules in biological networks. Compared with other highly cited module-finding tools, jActiveModules and Matisse, Walktrap-GM shows strong performance in the discovery of modules enriched with known cancer genes. Conclusions These results demonstrate that the Walktrap-GM algorithm identifies modules significantly enriched with cancer genes, their joint effects and promising candidate genes. The approach performs well when evaluated against similar tools and smaller overall module size allows for more specific functional annotation and facilitates the interpretation of these modules.

Cancer is a disease of aberrant gene expression. While the genetic causes of cancer have been intensively studied, it is becoming evident that a large proportion of cancer susceptibility cannot be attributed to variation in protein-coding sequences. This is highlighted by genome-wide association studies in cancer that reveal that more than 80% of cancer-associated SNPs occur in noncoding regions of the genome. In this review, we posit that a significant fraction of the genetic aetiology of cancer is exacted by noncoding regulatory sequences, particularly by long noncoding RNAs (lncRNAs). Recent studies indicate that several cancer risk loci are transcribed into lncRNAs and these transcripts play key roles in tumorigenesis. We discuss the epigenetic and other mechanisms through which lncRNAs function and how they contribute to each stage of cancer progression, understanding of which will be crucial for realising new opportunities in cancer diagnosis and treatment. Long noncoding RNAs play important roles in almost every aspect of cell biology from nuclear organisation and epigenetic regulation to post-transcriptional regulation and splicing, and we link these processes to the hallmarks and genetics of cancer. Finally, we highlight recent progress and future potential in the application of lncRNAs as therapeutic targets and diagnostic markers.

Thirty‐one seminars have been held in the 16 years since 1981. A principal interest from the beginning was the genetics of cancer, well before this subject became widely popular. This interest arose in part because of marked binational differences in type‐specific cancer rates, such as the very low rates among Japanese for Hodgkin's disease in the young, testicular cancer, Ewing's sarcoma, superficial spreading melanoma, chronic lymphocytic leukemia, and Wilms’ tumor (half the U.S. frequency). Three seminars were devoted to the seeming reciprocal relationship between B‐cell lymphoma (low in Japan) and certain autoimmune diseases (high in Japan), which is perhaps similar in origin to the male/female differences in the rates for these diseases. A seminar on Li‐Fraumeni syndrome led to the recognition of cases among Japanese pedigrees brought to the meeting, and generated a study of its occurrence in Japanese families with adrenocortical carcinoma in a child. Another seminar revealed a marked clustering of rare cancers in Werner's (premature aging) syndrome in Japan, and led to a binational study and analysis of case‐reports worldwide. Three seminars on pathology heightened appreciation of the importance of subclassifying cancer by subsite and subtype for racial and other comparisons. Four seminars on biostatistics in cancer research generated a substantial exchange of specialists and trainees in this field.

In the past forty to fifty years, clever scientific insight and innovation has rapidly advanced our understanding of the molecular mechanisms of cancer biology . The discoveries of oncogenes and tumor suppressors and the elucidation of their functions has greatly aided our understanding of the molecular etiology of primary tumors. In the last decade, there has been an explosion in the technology available to scientists to study the genetics of cancer cells at several different levels. It is now possible to study a particular cancer at the whole genome , transcriptome, and proteome levels. This vast increase in available information has led to significant advancements in our understanding of the genetic variations and mutations, which can drive the development of a primary tumor in patients.

The laboratory mouse is the premier model organism for understanding the genetic basis of human cancer and is a powerful platform for investigating novel targets for therapeutic intervention. Research using genetically engineered mouse models has led to key insights into the genetics of cancer susceptibility, the function of tumor suppressors and oncogenes, and therapy responses in pre-clinical and co-clinical studies. Patient Derived Xenografts (PDX) models are another model system for in vivo cancer studies. PDX models are created by implanting patient tumors into immunodeficient or humanized mouse hosts. PDX models are a powerful translational research platform for pre-clinical and co-clinical studies. The number of mouse models and the volume and heterogeneity of data related to the characterization of these models has increased dramatically in recent years, making integrated searches of these data and identifying relevant models a significant barrier to their effective use. The Mouse Tumor Biology database (MTB) (http://tumor.informatics.jax.org) provides on-line query tools to facilitate cohesive searches and visualization of these varied data, thus enabling the identification of novel mouse models of human cancer and potential therapeutic treatments. The Mouse Tumor Biology database is an expertly curated resource for information and data about genetically modified mouse strains and PDX models of human cancer. Enforcement of standard gene and strain nomenclature and use of controlled vocabularies within MTB enables complete and accurate searching of the published literature for relevant mouse models. MTB contains data from spontaneous or endogenously induced tumors from genetically defined mice including tumor classification, incidence and latency, tumor associated QTLs, pathology reports, images and genetic changes in the tumor (somatic) and background strain (germline) genomes. The PDX resource enables searches based on tumor type, cancer diagnosis, and genomic properties of the engrafted tumors. Information in MTB is obtained from curation of peer-reviewed scientific publications and from direct data submissions from individual investigators and large-scale programs. MTB contains over 71,000 Tumor Frequencies, and over 2,080 Pathology Reports with over 5,800 images from over 3,600 references. MTB also provides access to detailed clinical, pathological, expression and genomics data from over 450 PDX models. Information in MTB is integrated with cancer models data from other bioinformatics resources including PathBase, the Gene Expression Omnibus (GEO), and ArrayExpress. MTB is supported by NCI grant CA089713. Citation Format: Dale A. Begley, Debbie M. Krupke, Steven B. Neuhauser, Joel E. Richardson, John P. Sundberg, Janan T. Eppig, Carol J. Bult. The mouse tumor biology database (MTB): An integrated data resource for mouse and patient derived xenograft (PDX) models of human cancer. [abstract]. In: Proceedings of the 107th Annual Meeting of the American Association for Cancer Research; 2016 Apr 16-20; New Orleans, LA. Philadelphia (PA): AACR; Cancer Res 2016;76(14 Suppl):Abstract nr 631.

The heritability of cancers is usually affected by complex interactions between carcinogens and the host's genome. New aspects of the genetics of cancer pathogenesis, such as DNA methylation, and micro RNAs are increasingly recognized as important events. Chemotherapeutic drugs interfere with cell division in different ways, e.g. with the duplication of DNA or the separation of newly formed chromosomes. Most forms of chemotherapy target rapidly dividing cells and are not specific for cancer cells, although some degree of specificity may come from the inability of many cancer cells to repair DNA damage. Hence, chemotherapy has the potential to harm healthy tissues, especially those tissues that have a high replacement rate (e.g. intestinal lining). These cells usually repair themselves after chemotherapy.[1] DNA has long been considered a favored target for cancer chemotherapeutic agents. Indeed many of the most effective clinical agents, such as alkylating and interactive agents, are DNA interactive. Achieving the desired sequence specificity with DNA-interactive agents is considered to be one of the most formidable hurdles in the development of new agents to achieve therapeutic invention.[2]

In the UK, four in ten people will develop some form of cancer during their lifetime, with an individual's relative risk depending on many factors, including age, lifestyle and genetic make-up. Much research has gone into identifying the genes that are mutated in tumorigenesis with the over-whelming majority of genetically-modified (GM) mice in cancer research showing accelerated tumorigenesis or recapitulating key aspects of the tumorigenic process. Yet if six out of ten people will not develop some form of cancer during their lifetime, together with the fact that some cancer patients experience spontaneous regression/remission, it suggests there are ways of ‘resisting’ cancer. Indeed, there are wildtype, spontaneously-arising mutants and GM mice that show some form of ‘resistance’ to cancer. Identification of mice with increased resistance to cancer is a novel aspect of cancer research that is important in terms of providing both chemopreventative and therapeutic options. In this review we describe the different mouse lines that display a ‘cancer resistance’ phenotype and discuss the molecular basis of their resistance.

Cancer is a large group of diseases that result when cells divide out of control and acquire the ability to spread beyond their prescribed borders. Cancer is a genetic disease because it is caused by mutations, but it is rarely inherited because these mutations occur, in most cases, in somatic cells rather than in germ cells. Cancer affects one in three people during their lifetime and is the second leading cause of death in the United States. In women, the most common and most lethal cancers originate in the lung, breast, and colon. In men, cancers of the lung, prostate, and colon predominate. In sharp contrast to cancer, also called a malignant tumor, a benign tumor is defined as a collection of cells that grows out of control but does not spread into surrounding tissues.

Lung cancer and head and neck cancer have similar genotoxic risk factors. While the vast majority of lung cancers are caused by cigarette smoking alone, smoking together with heavy drinking are the major etiological agents of head and neck cancer. In addition, human papilloma virus (HPV) has been identified as an important causative factor of tonsillar carcinomas. In contrast, chromosomal instability and aneuploidy identifiable by DNA measurement are predominately associated with cancer progression. This selective review summarizes our studies that aimed to gain a better understanding of the biology and pathology of lung cancer and head and neck cancer. In particular, it was attempted (a) to develop a microscopy-based tumor classification system that provides insight into the genetics of cancer cells and in particular their DNA ploidy, (b) to apply this classification system to lung cancer and head and neck cancer and to correlate it with clinicopathological parameters and molecular biomarkers, and (c) to analyze molecular characteristics and in particular the presence of human papilloma virus in lung cancer and head and neck cancer. Therefore, we developed a core classification based on the semi-quantitative assessment of the size and type of tumor cell nuclei and mitoses. It was found that (1) nuclear and mitosis size correlated with the DNA content of the tumor cells, (2) tripolar mitoses were indicative of cancer with near-triploid DNA content, (3) morphological and DNA parameters indicating variability of the cancer genome were associated with poor prognosis of lung cancer patients, (4) HPV-positive head and neck squamous cell carcinomas were characterized by smaller tumor nuclei and reduced DNA amount compared to HPV-negative carcinomas, and (5) HPV is associated with lung cancer in certain geographical regions of the world.

The development of human cancer is generally considered to be the result of genetic mutations that cause a progressively more malignant phenotype. We propose that such genetic changes can be observed in a small number of lymphocytic metaphase plates. We have identified a specific chromosome marker formation in a primary endometrial adenocarcinoma obtained from a 74-year-old woman. After observing an isochromosome for 1q in the tumor cells, we predicted that in her lymphocytes this particular chromosome must show susceptibility to breakage. After 6 months, when lymphocytes were available from this patient, 4.0% of her metaphases exhibited chromatid breaks in the pericentromeric region of one homolog of chromosome 1, thus confirming our prediction. Since then, the primary endometrial tumor cell line has been passaged through nude mice and has become highly metastatic. Examination of tumors obtained from different organ sites of these mice has revealed that the same altered homolog 1 underwent various types of chromosome and chromatid aberrations, thereby confirming the presence of instability in this particular chromosome in this particular cancer. A detailed karyotypic evolution from normal lymphocyte cultures --> primary endometrial tumor --> highly metastatic endometrial tumor was therefore possible to construct. Our results further support the idea that peripheral blood lymphocytes can be used as the tissue for studying genetics of cancer predisposition.

Genetic predisposition controlled by susceptibility quantitative trait loci (QTLs) contributes to a large proportion of common cancers. Studies of genetics of cancer susceptibility, however, did not address systematically the relationship between susceptibility to cancers in different organs. We present five sets of data on genetic architecture of colon and lung cancer susceptibility in mice, humans and rats. They collectively show that the majority of genes for colon and lung cancer susceptibility are linked pair-wise and are likely identical or related. Four CcS/Dem recombinant congenic strains, each differing from strain BALB/cHeA by a different small random subset of ±12.5% of genes received from strain STS/A, suggestively show either extreme susceptibility or extreme resistance for both colon and lung tumors, which is unlikely if the two tumors were controlled by independent susceptibility genes. Indeed, susceptibility to lung cancer (Sluc) loci underlying the extreme susceptibility or resistance of such CcS/Dem strains, mapped in 226 (CcS-10 x CcS-19)F2 mice, co-localize with susceptibility to colon cancer (Scc) loci. Analysis of additional Sluc loci that were mapped in OcB/Dem strains and Scc loci in CcS/Dem strains, respectively, shows their widespread pair-wise co-localization (P = 0.0036). Finally, the majority of published human and rat colon cancer susceptibility genes map to chromosomal regions homologous to mouse Sluc loci. 12/12 mouse Scc loci, 9/11 human and 5/7 rat colon cancer susceptibility loci are close to a Sluc locus or its homologous site, forming 21 clusters of lung and colon cancer susceptibility genes from one, two or three species. Our data shows that cancer susceptibility QTLs can have much broader biological effects than presently appreciated. It also demonstrates the power of mouse genetics to predict human susceptibility genes. Comparison of molecular mechanisms of susceptibility genes that are organ-specific and those with trans-organ effects can provide a new dimension in understanding individual cancer susceptibility.

One hundred years ago, decades before the discovery of the structure of DNA, debate raged regarding how human traits were passed from one generation to the next. Phenotypes, including risk of disease, had long been recognized as having a familial component. Yet it was difficult to reconcile genetic segregation as described by Mendel with observations exhaustively documented by Karl Pearson and others regarding the normal distribution of human characteristics. In 1918, R. A. Fisher published his landmark article, "The Correlation Between Relatives on the Supposition of Mendelian Inheritance," bridging this divide and demonstrating that multiple alleles, all individually obeying Mendel's laws, account for the phenotypic variation observed in nature.Since that time, geneticists have sought to identify the link between genotype and phenotype. Trait-associated alleles vary in their frequency and degree of penetrance. Some minor alleles may approach a frequency of 50% in the human population, whereas others are present within only a few individuals. The spectrum for penetrance is similarly wide. These characteristics jointly determine the segregation pattern of a given trait, which, in turn, determine the method used to map the trait. Until recently, identification of rare, highly penetrant alleles was most practical. Revolutionary studies in genomics reported over the past decade have made interrogation of most of the spectrum of genetic variation feasible.The following article reviews recent discoveries in the genetic basis of inherited cancer risk and how these discoveries inform cancer biology and patient management. Although this article focuses on prostate cancer, the principles are generic for any cancer and, indeed, for any trait.