Looking beyond drivers and passengers in cancer genome sequencing data

The Function of the Immune System, Beyond Strategies Based on Cell-Autonomous Mechanisms, Determines Cancer Development: Immune Response and Cancer Development

Although cancer remains a challenging disease to treat, early detection and removal of primary tumors through surgery or chemotherapy/radiotherapy can offer hope for patients. The privilege paradigm in cancer biology suggests that cell-autonomous mechanisms play a central role in tumorigenesis. According to this paradigm, these cellular mechanisms are the primary focus for the prevention and treatment of cancers. However, this point of view does not present a comprehensive theory for the initiation of cancer and an effective therapeutic strategy. Having an incomplete understanding of the etiology of cancer, it is essential to re-examine previous assumptions about carcinogenesis and develop new, practical theories that can account for all available clinical and experimental evidence. This will not only help to gain a better understanding of the disease, but also offer new avenues for treatment. This review provides evidence suggesting a shift in focus from a cell-autonomous mechanism to systemic mechanisms, particularly the immune system, that are involved in cancer formation.

Cold Tumour Phenotype Explained Through Whole Genome Sequencing in Clinical Nasopharyngeal Cancer: A Preliminary Study

Introduction

Nasopharyngeal cancer (NPC) is a complex cancer due to its unique genomic features and association with the Epstein-Barr virus (EBV). Despite therapeutic advancements, NPC prognosis remains poor, necessitating a deeper understanding of its genomics. Here, we present a comprehensive whole genome sequencing (WGS) view of NPC genomics and its correlation with the phenotype.

Methods

This study involved WGS of a clinical NPC biopsy specimen. Sequencing was carried out using a long read sequencer from Oxford Nanopore. Analysis of the variants involved correlation with the phenotype of NPC.

Results

A loss of genes within chromosome 6 from copy number variation (CNV) was found. The lost genes included HLA-A, HLA-B, and HLA-C, which work in the antigen presentation process. This loss of the major histocompatibility complex (MHC) apparatus resulted in the tumour's ability to evade immune recognition. The tumour exhibited an immunologically "cold" phenotype, with mild tumour-infiltrating lymphocytes, supporting the possible etiology of loss of antigen presentation capability. Furthermore, the driver mutation PIK3CA gene was identified along with various other gene variants affecting numerous signaling pathways.

Discussion

Comprehensive WGS was able to detect various mutations and genomic losses, which could explain tumour progression and immune evasion ability. Furthermore, the study identified the loss of other genes related to cancer and immune pathways, emphasizing the complexity of NPC genomics. In conclusion, this study underscores the significance of MHC class I gene loss and its probable correlation with the cold tumour phenotype observed in NPC.

Transcriptional state dynamics lead to heterogeneity and adaptive tumor evolution in urothelial bladder carcinoma

Intra-tumor heterogeneity contributes to treatment failure and poor survival in urothelial bladder carcinoma (UBC). Analyzing transcriptome from a UBC cohort, we report that intra-tumor transcriptomic heterogeneity indicates co-existence of tumor cells in epithelial and mesenchymal-like transcriptional states and bi-directional transition between them occurs within and between tumor subclones. We model spontaneous and reversible transition between these partially heritable states in cell lines and characterize their population dynamics. SMAD3, KLF4 and PPARG emerge as key regulatory markers of the transcriptional dynamics. Nutrient limitation, as in the core of large tumors, and radiation treatment perturb the dynamics, initially selecting for a transiently resistant phenotype and then reconstituting heterogeneity and growth potential, driving adaptive evolution. Dominance of transcriptional states with low PPARG expression indicates an aggressive phenotype in UBC patients. We propose that phenotypic plasticity and dynamic, non-genetic intra-tumor heterogeneity modulate both the trajectory of disease progression and adaptive treatment response in UBC.

Familial CCM Genes Might Not Be Main Drivers for Pathogenesis of Sporadic CCMs-Genetic Similarity between Cancers and Vascular Malformations

Cerebral cavernous malformations (CCMs) are abnormally dilated intracranial capillaries that form cerebrovascular lesions with a high risk of hemorrhagic stroke. Recently, several somatic "activating" gain-of-function (GOF) point mutations in PIK3CA (phosphatidylinositol-4, 5-bisphosphate 3-kinase catalytic subunit p110α) were discovered as a dominant mutation in the lesions of sporadic forms of cerebral cavernous malformation (sCCM), raising the possibility that CCMs, like other types of vascular malformations, fall in the PIK3CA-related overgrowth spectrum (PROS). However, this possibility has been challenged with different interpretations. In this review, we will continue our efforts to expound the phenomenon of the coexistence of gain-of-function (GOF) point mutations in the PIK3CA gene and loss-of-function (LOF) mutations in CCM genes in the CCM lesions of sCCM and try to delineate the relationship between mutagenic events with CCM lesions in a temporospatial manner. Since GOF PIK3CA point mutations have been well studied in reproductive cancers, especially breast cancer as a driver oncogene, we will perform a comparative meta-analysis for GOF PIK3CA point mutations in an attempt to demonstrate the genetic similarities shared by both cancers and vascular anomalies.

Distinct non-clock-like signatures of the basal cell carcinomas from three sisters with a lethal Gorlin-Goltz syndrome

Background

Gorlin-Goltz syndrome (GS) is an inherited disease characterized by predisposition to basal cell carcinomas (BCCs) and various developmental defects, whose numerous disease-causing PTCH1 mutations have been identified in the hedgehog (Hh) signaling pathway.

Methods

In this study, whole exome sequencing was used to screen for both somatic and germline deleterious mutations in three sisters with a lethal GS. The mutations we found were confirmed by subcloning and Sanger sequencing of the genomic DNA. RNA-seq was performed to profile gene expression in paired BCCs samples and the expression levels for selected genes were validated by quantitative PCR.

Results

The clinical and histopathologic features were analyzed for the proband in the three-generation GS family. We identified the insertion mutation PTCH1 c.1341dupA (p. L448Tfs*49), which segregated with BCC phenotype and contributed to the death of two in four patients from a Chinese family with GS. Compared with adjacent non-cancerous tissues (ANCT), four second-hit mutations were found in four of the six pairs of BCC from three patients. Of note, somatic genomic alterations in all six BCC samples were mainly clustered into non-clock-like Signature 7 (ultraviolet mutagenesis) and 11 (related to certain alkylating agents). Both RNA-seq and quantitative RT-PCR confirmed that the mRNA levels of PTCH1 and its effector GLI1 were markedly upregulated in six pairs of BCC samples versus ANCT.

Conclusions

The distinct non-clock-like signatures of BCCs indicated that GS was not a life-threatening illness. The main reasons for untimely death of GS patients were PTCH1 mutation, exposure to intense ultraviolet radiationand the poor economic conditions.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12920-022-01324-7.

Signatures Beyond Oncogenic Mutations in Cell-Free DNA Sequencing for Non-Invasive, Early Detection of Cancer

Early detection of cancer saves lives, but an effective detection strategy in public health settings requires a delicate balance - periodic screening should neither miss rapidly progressing disease nor fail to detect rare tumors at unusual locations; on the other hand, even a modest false positive rate carries risks of over-diagnosis and over-treatment of relatively indolent non-malignant disease. Genomic profiling of cell-free DNA from liquid biopsy using massively parallel sequencing is emerging as an attractive, non-invasive screening platform for sensitive detection of multiple types of cancer in a single assay. Genomic data from cell-free DNA can not only identify oncogenic mutation status, but also additional molecular signatures related to potential tissue of origin, the extent of clonal growth, and malignant disease states. Utilization of the full potential of the molecular signatures from cfDNA sequencing data can guide clinical management strategies for targeted follow-ups using imaging or molecular marker-based diagnostic platforms and treatment options.

Monitoring of clonal evolution of acute myeloid leukemia identifies the leukemia subtype, clinical outcome and potential new drug targets for post-remission strategies or relapse

In cases of treatment failure in acute myeloid leukemia (AML), the utility of mutational profiling in primary refractoriness and relapse is not established. We undertook a perspective study using next-generation sequencing (NGS) of clinical follow-up samples (n=91) from 23 patients with AML with therapeutic failure to cytarabine plus idarubicin or fludarabine. Cases of primary refractoriness to treatment were associated with a lower number of DNA variants at diagnosis than cases of relapse (median 1.67 and 3.21, respectively, P=0.029). The most frequently affected pathways in patients with primary refractoriness were signaling, transcription and tumor suppression, whereas methylation and splicing pathways were mainly implicated in relapsed patients. New therapeutic targets, either by an approved drug or within clinical trials, were not identified in any of the cases of refractoriness (zero of ten); however, eight potential new targets were found in five relapsed patients (five of 13, P=0.027): one IDH2, three SF3B1, two KRAS, one KIT and one JAK2. Sixty-five percent of all variants detected at diagnosis were not detected at complete response. Specifically, 100% of variants in EZH2, RUNX1, VHL, FLT3, ETV6, U2AF1, PHF6 and SF3B1 disappeared at complete response, indicating their potential use as markers to evaluate minimal residual disease for follow-up of AML. Molecular follow-up using a custom NGS myeloid panel of 32 genes in the post-treatment evaluation of AML can help in the stratification of prognostic risk, the selection of minimal residual disease markers to monitor the response to treatment and guide post-remission strategies targeting AML, and the selection of new drugs for leukemia relapse.

Drivers of dynamic intratumor heterogeneity and phenotypic plasticity

Cancer is a clonal disease, i.e., all tumor cells within a malignant lesion trace their lineage back to a precursor somatic cell that acquired oncogenic mutations during development and aging. And yet, those tumor cells tend to have genetic and nongenetic variations among themselves-which is denoted as intratumor heterogeneity. Although some of these variations are inconsequential, others tend to contribute to cell state transition and phenotypic heterogeneity, providing a substrate for somatic evolution. Tumor cell phenotypes can dynamically change under the influence of genetic mutations, epigenetic modifications, and microenvironmental contexts. Although epigenetic and microenvironmental changes are adaptive, genetic mutations are usually considered permanent. Emerging reports suggest that certain classes of genetic alterations show extensive reversibility in tumors in clinically relevant timescales, contributing as major drivers of dynamic intratumor heterogeneity and phenotypic plasticity. Dynamic heterogeneity and phenotypic plasticity can confer resistance to treatment, promote metastasis, and enhance evolvability in cancer. Here, we first highlight recent efforts to characterize intratumor heterogeneity at genetic, epigenetic, and microenvironmental levels. We then discuss phenotypic plasticity and cell state transition by tumor cells, under the influence of genetic and nongenetic determinants and their clinical significance in classification of tumors and therapeutic decision-making.

Providing an optimized model to detect driver genes from heterogeneous cancer samples using restriction in subspace learning

Extracting the drivers from genes with mutation, and segregation of driver and passenger genes are known as the most controversial issues in cancer studies. According to the heterogeneity of cancer, it is not possible to identify indicators under a group of associated drivers, in order to identify a group of patients with diseases related to these subgroups. Therefore, the precise identification of the related driver genes using artificial intelligence techniques is still considered as a challenge for researchers. In this research, a new method has been developed using the subspace learning method, unsupervised learning, and with more constraints. Accordingly, it has been attempted to extract the driver genes with more precision and accurate results. The obtained results show that the proposed method is more to predict the driver genes and subgroups of driver genes which have the highest degree of overlap due to p-value with known driver genes in valid databases. Driver genes are the benchmark of MsigDB which have more overlap compared to them as selected driver genes. In this article, in addition to including the driver genes defined in previous work, introduce newer driver genes. The minister will define newer groups of driver genes compared to other methods the p-value of the proposed method was 9.21e-7 better than previous methods for 200 genes. Due to the overlap and newer driver genes and driver gene group and subgroups. The results show that the p value of the proposed method is about 2.7 times less than the driver sub method due to overlap, indicating that the proposed method can identify driver genes in cancerous tumors with greater accuracy and reliability.

UBE2S interacting with TRIM28 in the nucleus accelerates cell cycle by ubiquitination of p27 to promote hepatocellular carcinoma development

Genomic sequencing analysis of tumors provides potential molecular therapeutic targets for precision medicine. However, identifying a key driver gene or mutation that can be used for hepatocellular carcinoma (HCC) treatment remains difficult. Here, we performed whole-exome sequencing on genomic DNA obtained from six pairs of HCC and adjacent tissues and identified two novel somatic mutations of UBE2S (p. Gly57Ala and p. Lys63Asn). Predictions of the functional effects of the mutations showed that two amino-acid substitutions were potentially deleterious. Further, we observed that wild-type UBE2S, especially in the nucleus, was significantly higher in HCC tissues than that in adjacent tissues and closely related to the clinicopathological features of patients with HCC. Functional assays revealed that overexpression of UBE2S promoted the proliferation, invasion, metastasis, and G1/S phase transition of HCC cells in vitro, and promoted the tumor growth significantly in vivo. Mechanistically, UBE2S interacted with TRIM28 in the nucleus, both together enhanced the ubiquitination of p27 to facilitate its degradation and cell cycle progression. Most importantly, the small-molecule cephalomannine was found by a luciferase-based sensitive high-throughput screen (HTS) to inhibit UBE2S expression and significantly attenuate HCC progression in vitro and in vivo, which may represent a promising strategy for HCC therapy.

Characteristics of mutational signatures of unknown etiology

Although not all somatic mutations are cancer drivers, their mutational signatures, i.e. the patterns of genomic alterations at a genome-wide scale, provide insights into past exposure to mutagens, DNA damage and repair processes. Computational deconvolution of somatic mutation patterns and expert curation pan-cancer studies have identified a number of mutational signatures associated with point mutations, dinucleotide substitutions, insertions and deletions, and rearrangements, and have established etiologies for a subset of these signatures. However, the mechanisms underlying nearly one-third of all mutational signatures are not yet understood. The signatures with established etiology and those with hitherto unknown origin appear to have some differences in strand bias, GC content and nucleotide context diversity. It is possible that some of the hitherto ‘unknown’ signatures predominantly occur outside gene regions. While nucleotide contexts might be adequate to establish etiologies of some mutational signatures, in other cases additional features, such as broader (epi)genomic contexts, including chromatin, replication timing, processivity and local mutational patterns, may help fully understand the underlying DNA damage and repair processes. Nonetheless, remarkable progress in characterization of mutational signatures has provided fundamental insights into the biology of cancer, informed disease etiology and opened up new opportunities for cancer prevention, risk management, and therapeutic decision making.

Non-Genetic Intra-Tumor Heterogeneity Is a Major Predictor of Phenotypic Heterogeneity and Ongoing Evolutionary Dynamics in Lung Tumors

Impacts of genetic and non-genetic intra-tumor heterogeneity (ITH) on tumor phenotypes and evolvability remain debated. We analyze ITH in lung squamous cell carcinoma at the levels of genome, transcriptome, and tumor-immune interactions and histopathological characteristics by multi-region bulk and single-cell sequencing. Genomic heterogeneity alone is a weak indicator of intra-tumor non-genetic heterogeneity at immune and transcriptomic levels that impact multiple cancer-related pathways, including those related to proliferation and inflammation, which in turn contribute to intra-tumor regional differences in histopathology and subtype classification. Tumor subclones have substantial differences in proliferation score, suggestive of non-neutral clonal dynamics. Proliferation and other cancer-related pathways also show intra-tumor regional differences, sometimes even within the same subclones. Neo-epitope burden negatively correlates with immune infiltration, indicating immune-mediated purifying selection on somatic mutations. Taken together, our observations suggest that non-genetic heterogeneity is a major determinant of heterogeneity in histopathological characteristics and impacts evolutionary dynamics in lung cancer.

Inferring subgroup-specific driver genes from heterogeneous cancer samples via subspace learning with subgroup indication

MOTIVATION

Detecting driver genes from gene mutation data is a fundamental task for tumorigenesis research. Due to the fact that cancer is a heterogeneous disease with various subgroups, subgroup-specific driver genes are the key factors in the development of precision medicine for heterogeneous cancer. However, the existing driver gene detection methods are not designed to identify subgroup specificities of their detected driver genes, and therefore cannot indicate which group of patients is associated with the detected driver genes, which is difficult to provide specifically clinical guidance for individual patients.

RESULTS

By incorporating the subspace learning framework, we propose a novel bioinformatics method called DriverSub, which can efficiently predict subgroup-specific driver genes in the situation where the subgroup annotations are not available. When evaluated by simulation datasets with known ground truth and compared with existing methods, DriverSub yields the best prediction of driver genes and the inference of their related subgroups. When we apply DriverSub on the mutation data of real heterogeneous cancers, we can observe that the predicted results of DriverSub are highly enriched for experimentally validated known driver genes. Moreover, the subgroups inferred by DriverSub are significantly associated with the annotated molecular subgroups, indicating its capability of predicting subgroup-specific driver genes.

AVAILABILITY AND IMPLEMENTATION

The source code is publicly available at https://github.com/JianingXi/DriverSub.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Mutational signature SBS8 predominantly arises due to late replication errors in cancer

Although a majority of somatic mutations in cancer are passengers, their mutational signatures provide mechanistic insights into mutagenesis and DNA repair processes. Mutational signature SBS8 is common in most cancers, but its etiology is debated. Incorporating genomic, epigenomic, and cellular process features for multiple cell-types we develop genome-wide composite epigenomic context-maps relevant for mutagenesis and DNA repair. Analyzing somatic mutation data from multiple cancer types in their epigenomic contexts, we show that SBS8 preferentially occurs in gene-poor, lamina-proximal, late replicating heterochromatin domains. While SBS8 is uncommon among mutations in non-malignant tissues, in tumor genomes its proportions increase with replication timing and speed, and checkpoint defects further promote this signature - suggesting that SBS8 probably arises due to uncorrected late replication errors during cancer progression. Our observations offer a potential reconciliation among different perspectives in the debate about the etiology of SBS8 and its relationship with other mutational signatures.

Prevention of tumor risk associated with the reprogramming of human pluripotent stem cells

Human pluripotent embryonic stem cells have two special features: self-renewal and pluripotency. It is important to understand the properties of pluripotent stem cells and reprogrammed stem cells. One of the major problems is the risk of reprogrammed stem cells developing into tumors. To understand the process of differentiation through which stem cells develop into cancer cells, investigators have attempted to identify the key factors that generate tumors in humans. The most effective method for the prevention of tumorigenesis is the exclusion of cancer cells during cell reprogramming. The risk of cancer formation is dependent on mutations of oncogenes and tumor suppressor genes during the conversion of stem cells to cancer cells and on the environmental effects of pluripotent stem cells. Dissecting the processes of epigenetic regulation and chromatin regulation may be helpful for achieving correct cell reprogramming without inducing tumor formation and for developing new drugs for cancer treatment. This review focuses on the risk of tumor formation by human pluripotent stem cells, and on the possible treatment options if it occurs. Potential new techniques that target epigenetic processes and chromatin regulation provide opportunities for human cancer modeling and clinical applications of regenerative medicine.

pMHC Structural Comparisons as a Pivotal Element to Detect and Validate T-Cell Targets for Vaccine Development and Immunotherapy-A New Methodological Proposal

The search for epitopes that will effectively trigger an immune response remains the “El Dorado” for immunologists. The development of promising immunotherapeutic approaches requires the appropriate targets to elicit a proper immune response. Considering the high degree of HLA/TCR diversity, as well as the heterogeneity of viral and tumor proteins, this number will invariably be higher than ideal to test. It is known that the recognition of a peptide-MHC (pMHC) by the T-cell receptor is performed entirely in a structural fashion, where the atomic interactions of both structures, pMHC and TCR, dictate the fate of the process. However, epitopes with a similar composition of amino acids can produce dissimilar surfaces. Conversely, sequences with no conspicuous similarities can exhibit similar TCR interaction surfaces. In the last decade, our group developed a database and in silico structural methods to extract molecular fingerprints that trigger T-cell immune responses, mainly referring to physicochemical similarities, which could explain the immunogenic differences presented by different pMHC-I complexes. Here, we propose an immunoinformatic approach that considers a structural level of information, combined with an experimental technology that simulates the presentation of epitopes for a T cell, to improve vaccine production and immunotherapy efficacy.

The anaphase-promoting complex: A key mitotic regulator associated with somatic mutations occurring in cancer

The anaphase-promoting complex/cyclosome (APC/C) is an E3 ubiquitin ligase that helps control chromosome separation and exit from mitosis in many different kinds of organisms, including yeast, flies, worms, and humans. This review represents a new perspective on the connection between APC/C subunit mutations and cancer. The complex nature of APC/C and limited mutation analysis of its subunits has made it difficult to determine the relationship of each subunit to cancer. In this work, cancer genomic data were examined to identify APC/C subunits with a greater than 5% alteration frequency in 11 representative cancers using the cBioPortal database. Using the Genetic Determinants of Cancer Patient Survival database, APC/C subunits were also studied and found to be significantly associated with poor patient prognosis in several cases. In comparing these two kinds of cancer genomics data to published large-scale genomic analyses looking for cancer driver genes, ANAPC1 and ANAPC3/CDC27 stood out as being represented in all three types of analyses. Seven other subunits were found to be associated both with >5% alteration frequency in certain cancers and being associated with an effect on cancer patient prognosis. The aim of this review is to provide new approaches for investigators conducting in vivo studies of APC/C subunits and cancer progression. In turn, a better understanding of these APC/C subunits and their role in different cancers will help scientists design drugs that are more precisely targeted to certain cancers, using APC/C mutation status as a biomarker.

Potential application of cell reprogramming techniques for cancer research

The ability to control the transition from an undifferentiated stem cell to a specific cell fate is one of the key techniques that are required for the application of interventional technologies to regenerative medicine and the treatment of tumors and metastases and of neurodegenerative diseases. Reprogramming technologies, which include somatic cell nuclear transfer, induced pluripotent stem cells, and the direct reprogramming of specific cell lineages, have the potential to alter cell plasticity in translational medicine for cancer treatment. The characterization of cancer stem cells (CSCs), the identification of oncogene and tumor suppressor genes for CSCs, and the epigenetic study of CSCs and their microenvironments are important topics. This review summarizes the application of cell reprogramming technologies to cancer modeling and treatment and discusses possible obstacles, such as genetic and epigenetic alterations in cancer cells, as well as the strategies that can be used to overcome these obstacles to cancer research.

Mutation Signatures Depend on Epigenomic Contexts

Mutation signatures - the patterns of acquired genetic changes in somatic genomes - provide critical insights into DNA repair defects and exposure to mutagenic processes during development, aging, and cancer progression. Efforts to decipher the etiology of the emerging computationally predicted mutation signatures in cancer genomes are currently underway. Since chromatin and epigenomic contexts influence DNA damage and repair pathway choices, taking both epigenomic and sequence contexts of the mutations into consideration is likely to benefit interpretation of mutation signatures.

Genomic and Bioinformatics Approaches for Analysis of Genes Associated With Cancer Risks Following Exposure to Tobacco Smoking

Cancer is a significant health problem in the Middle East and global population. It is well established that there is a direct link between tobacco smoking and cancer, which will continue to pose a significant threat to human health. The impact of long-term exposure to tobacco smoke on the risk of cancer encouraged the study of biomarkers for vulnerable individuals to tobacco smoking, especially children, who are more susceptible than adults to the action of environmental carcinogens. The carcinogens in tobacco smoke condensate induce DNA damage and play a significant role in determining the health and well-being of smokers, non-smoker, and primarily children. Cancer is a result of genomic and epigenomic malfunctions that lead to an initial premalignant condition. Although premalignancy genetic cascade is a much-delayed process, it will end with adverse health consequences. In addition to the DNA damage and mutations, tobacco smoke can cause changes in the DNA methylation and gene expression associated with cancer. The genetic events hint on the possible use of genomic–epigenomic changes in genes related to cancer, in predicting cancer risks associated with exposure to tobacco smoking. Bioinformatics provides indispensable tools to identify the cascade of expressed genes in active smokers and non-smokers and could assist the development of a framework to manage this cascade of events linked with the evolvement of disease including cancer. The aim of this mini review is to cognize the essential genomic processes and health risks associated with tobacco smoking and the implications of bioinformatics in cancer prediction, prevention, and intervention.

Nuclear topology modulates the mutational landscapes of cancer genomes

Nuclear organization of genomic DNA affects DNA damage and repair processes, and yet its impact on mutational landscapes in cancer genomes remains unclear. Here we analyzed genome-wide somatic mutations from 366 samples of 6 cancer types. We found that lamina-associated regions, which are typically localized at the nuclear periphery, displayed higher somatic mutation frequencies compared to the inter-lamina regions at the nuclear core. This effect remained even after adjusting for features such as GC%, chromatin, and replication timing. Furthermore, mutational signatures differed between the nuclear core and periphery, indicating differences in the patterns of DNA damage and/or DNA repair processes. For instance, smoking and UV-related signatures were more enriched in the nuclear periphery. Substitutions at certain motifs were also more common in the nuclear periphery. Taken together, we found that the nuclear architecture influences mutational landscapes in cancer genomes beyond the effects already captured by chromatin and replication timing.

Genetics of common complex diseases: a view from Iceland

In the past decade, large scale genotyping has led to discoveries of numerous sequence variants that confer increased risk of many common complex diseases. Interestingly, a substantial proportion of pioneering genetic work has originated from the small nation of Iceland and has been facilitated by an extensive genealogy database. We provide examples of relevant observations made so far in several major disease categories central to internal medicine practice. Some of these findings offer new mechanistic clues into the pathophysiology of common disorders and may suggest novel approaches in diagnosis and drug therapy. However, a number of unresolved issues remain that will be subject of future research, driven by recent advances in high-throughput sequencing of the genome. At the same time, we are ready to begin transforming the abundant existing genetic data into practical clinical knowledge with the aim of improving the delivery of medical care. The era of precision medicine has arrived.

Cancer cell reprogramming to identify the genes competent for generating liver cancer stem cells

The cancer stem cell (CSC) hypothesis postulates that cancer originates from the malignant transformation of stem/progenitor cells and is considered to apply to many cancers, including liver cancer. Identification that CSCs are responsible for drug resistance, metastasis, and secondary tumor appearance suggests that these populations are novel obligatory targets for the treatment of cancer. Here, we describe our new method for identifying potential CSC candidates. The reprogramming of cancer cells via induced pluripotent stem cell (iPSC) technology is a novel therapy for the treatment and for the study of CSC-related genes. This technology has advantages for studying the interactions between CSC-related genes and the cancer niche microenvironment. This technology may also provide a useful platform for studying the genes involved in the generation of CSCs before and after reprogramming, and for elucidating the mechanisms underlying cancer initiation and progression. The present review summarizes the current understanding of transcription factors involved in the generation of liver CSCs from liver cancer cell-derived iPSCs and how these contribute to oncogenesis, and discusses the modeling of liver cancer development.