Exploring the genomes of cancer cells: progress and promise

Spatiotemporal dynamics of clonal selection and diversification in normal endometrial epithelium

It has become evident that somatic mutations in cancer-associated genes accumulate in the normal endometrium, but spatiotemporal understanding of the evolution and expansion of mutant clones is limited. To elucidate the timing and mechanism of the clonal expansion of somatic mutations in cancer-associated genes in the normal endometrium, we sequence 1311 endometrial glands from 37 women. By collecting endometrial glands from different parts of the endometrium, we show that multiple glands with the same somatic mutations occupy substantial areas of the endometrium. We demonstrate that “rhizome structures”, in which the basal glands run horizontally along the muscular layer and multiple vertical glands rise from the basal gland, originate from the same ancestral clone. Moreover, mutant clones detected in the vertical glands diversify by acquiring additional mutations. These results suggest that clonal expansions through the rhizome structures are involved in the mechanism by which mutant clones extend their territories. Furthermore, we show clonal expansions and copy neutral loss-of-heterozygosity events occur early in life, suggesting such events can be tolerated many years in the normal endometrium. Our results of the evolutionary dynamics of mutant clones in the human endometrium will lead to a better understanding of the mechanisms of endometrial regeneration during the menstrual cycle and the development of therapies for the prevention and treatment of endometrium-related diseases.

Through regeneration, the endometrium accumulates somatic mutations that can lead to diseases like endometriosis and cancer. Here, the authors use genomics to analyse normal endometrial glands from different patient cohorts, detect rhizome structures with common clonal ancestors and infer clonal expansion dynamics.

Recent advances in targeted nanotherapeutic approaches for breast cancer management

Breast cancer is the most commonly occurring tumor disease worldwide. Breast cancer is currently managed by conventional chemotherapy, which is inadequate in curbing this heterogeneous disease and results in off-site toxic effects, suggesting effective treatment approaches with better therapeutic profiles are needed. This review, therefore, focuses on the recent advancements in delivering therapeutics to the target site using passive and/or active targeted nanodrug-delivery systems to ameliorate endolysosomal escape. In addition, recent strategies in targeting breast cancer stem cells are discussed. The role of naturally cell-secreted nanovesicles (exosomes) in the management of triple-negative breast cancer is also discussed.

Cancer Evo-Dev: A Theory of Inflammation-Induced Oncogenesis

Chronic inflammation is a prerequisite for the development of cancers. Here, we present the framework of a novel theory termed as Cancer Evolution-Development (Cancer Evo-Dev) based on the current understanding of inflammation-related carcinogenesis, especially hepatocarcinogenesis induced by chronic infection with hepatitis B virus. The interaction between genetic predispositions and environmental exposures, such as viral infection, maintains chronic non-resolving inflammation. Pollution, metabolic syndrome, physical inactivity, ageing, and adverse psychosocial exposure also increase the risk of cancer via inducing chronic low-grade smoldering inflammation. Under the microenvironment of non-resolving inflammation, pro-inflammatory factors facilitate the generation of somatic mutations and viral mutations by inducing the imbalance between the mutagenic forces such as cytidine deaminases and mutation-correcting forces including uracil-DNA glycosylase. Most cells with somatic mutations and mutated viruses are eliminated in survival competition. Only a small percentage of mutated cells survive, adapt to the hostile environment, retro-differentiate, and function as cancer-initiating cells via altering signaling pathways. These cancer-initiating cells acquire stem-ness, reprogram metabolic patterns, and affect the microenvironment. The carcinogenic process follows the law of "mutation-selection-adaptation". Chronic physical activity reduces the levels of inflammation via upregulating the activity and numbers of NK cells and lymphocytes and lengthening leukocyte telomere; downregulating proinflammatory cytokines including interleukin-6 and senescent lymphocytes especially in aged population. Anti-inflammation medication reduces the occurrence and recurrence of cancers. Targeting cancer stemness signaling pathways might lead to cancer eradication. Cancer Evo-Dev not only helps understand the mechanisms by which inflammation promotes the development of cancers, but also lays the foundation for effective prophylaxis and targeted therapy of various cancers.

The Evolution and Future of Targeted Cancer Therapy: From Nanoparticles, Oncolytic Viruses, and Oncolytic Bacteria to the Treatment of Solid Tumors

While many classes of chemotherapeutic agents exist to treat solid tumors, few can generate a lasting response without substantial off-target toxicity despite significant scientific advancements and investments. In this review, the paths of development for nanoparticles, oncolytic viruses, and oncolytic bacteria over the last 20 years of research towards clinical translation and acceptance as novel cancer therapeutics are compared. Novel nanoparticle, oncolytic virus, and oncolytic bacteria therapies all start with a common goal of accomplishing therapeutic drug activity or delivery to a specific site while avoiding off-target effects, with overlapping methodology between all three modalities. Indeed, the degree of overlap is substantial enough that breakthroughs in one therapeutic could have considerable implications on the progression of the other two. Each oncotherapeutic modality has accomplished clinical translation, successfully overcoming the potential pitfalls promising therapeutics face. However, once studies enter clinical trials, the data all but disappears, leaving pre-clinical researchers largely in the dark. Overall, the creativity, flexibility, and innovation of these modalities for solid tumor treatments are greatly encouraging, and usher in a new age of pharmaceutical development.

Significance and limitations of the use of next-generation sequencing technologies for detecting mutational signatures

Next generation sequencing technologies (NGS) have been critical in characterizing the genomic landscape and untangling the genetic heterogeneity of human cancer. Since its advent, NGS has played a pivotal role in identifying the patterns of somatic mutations imprinted on cancer genomes and in deciphering the signatures of the mutational processes that have generated these patterns. Mutational signatures serve as phenotypic molecular footprints of exposures to environmental factors as well as deficiency and infidelity of DNA replication and repair pathways. Since the first roadmap of mutational signatures in human cancer was generated from whole-genome and whole-exome sequencing data, there has been a growing interest to extract mutational signatures from other NGS technologies such as targeted panel sequencing, RNA sequencing, single-cell sequencing, duplex sequencing, reduced representation sequencing, and long-read sequencing. Many of these technologies have their inherent sequencing biases and produce technical artifacts that can confound the extraction of reliable and interpretable mutational signatures. In this review, we highlight the relevance, limitations, and prospects of using different NGS technologies for examining mutational patterns and for deciphering mutational signatures.

Tumor models in various Drosophila tissues

The development of cancer is a complex multistage process. Over the past few decades, the model organism Drosophila melanogaster has been crucial in identifying cancer-related genes and pathways and elucidating mechanisms underlying growth regulation in development. Investigations using Drosophila has yielded new insights into the molecular mechanisms involved in tumor initiation and progression. In this review, we describe various tumor models that have been developed in recent years using different Drosophila tissues, such as the imaginal tissue, the neural tissue, the gut, the ovary, and hematopoietic cells. We discuss underlying genetic alterations, cancer-like characteristics, as well as similarities and key differences among these models. We also discuss how disruptions in stem cell division and differentiation result in tumor formation in diverse tissues, and highlight new concepts developed using the fly model to understand context-dependent tumorigenesis. We further discuss the progress made in Drosophila to explore tumor-host interactions that involve the innate immune response to tumor growth and the cachexia wasting phenotype. This article is categorized under: Cancer > Genetics/Genomics/Epigenetics Cancer > Stem Cells and Development Cancer > Molecular and Cellular Physiology.

The Genomic Processes of Biological Invasions: From Invasive Species to Cancer Metastases and Back Again

The concept of invasion is useful across a broad range of contexts, spanning from the fine scale landscape of cancer tumors up to the broader landscape of ecosystems. Invasion biology provides extraordinary opportunities for studying the mechanistic basis of contemporary evolution at the molecular level. Although the field of invasion genetics was established in ecology and evolution more than 50 years ago, there is still a limited understanding of how genomic level processes translate into invasive phenotypes across different taxa in response to complex environmental conditions. This is largely because the study of most invasive species is limited by information about complex genome level processes. We lack good reference genomes for most species. Rigorous studies to examine genomic processes are generally too costly. On the contrary, cancer studies are fortified with extensive resources for studying genome level dynamics and the interactions among genetic and non-genetic mechanisms. Extensive analysis of primary tumors and metastatic samples have revealed the importance of several genomic mechanisms including higher mutation rates, specific types of mutations, aneuploidy or whole genome doubling and non-genetic effects. Metastatic sites can be directly compared to primary tumor cell counterparts. At the same time, clonal dynamics shape the genomics and evolution of metastatic cancers. Clonal diversity varies by cancer type, and the tumors’ donor and recipient tissues. Still, the cancer research community has been unable to identify any common events that provide a universal predictor of “metastatic potential” which parallels findings in evolutionary ecology. Instead, invasion in cancer studies depends strongly on context, including order of events and clonal composition. The detailed studies of the behavior of a variety of human cancers promises to inform our understanding of genome level dynamics in the diversity of invasive species and provide novel insights for management.

The effect of the TP53 and RB1 mutations on the survival of hepatocellular carcinoma patients with different racial backgrounds

Background

Racial disparities in the survival of patients with hepatocellular carcinoma (HCC) exist. Gene mutations have a profound effect on carcinogenesis, are easily affected by environment and etiology factors, and may result in survival divergences among patients with different racial backgrounds. This report explores the effects of gene mutations on the survival of American Caucasians and Asian patients.

Methods

The sequencing and clinical data of 336 HCC patients were obtained from The Cancer Genome Atlas (TCGA) database. The sequencing data was subject to gene mutation profiling, and an analysis of immune cell infiltration was conducted. A multivariate analysis was performed to assess the independent effects of gene mutations on patients' overall survival (OS) and disease-free survival (DFS).

Results

Asian HCC patients had a significantly higher level of TP53 mutation frequency than Caucasian HCC patients (Asian vs. Caucasian, 39% vs. 23%; P=0.003). The TP53 mutation was associated with shorter OS [hazard ratio (HR), 2.33; 95% confidence interval (CI), 1.36-3.97; P=0.002] and DFS (HR, 2.2; 95% CI, 1.38-3.51; P<0.001) in Caucasian HCC patients, but had no effect on Asian HCC patients' survival. Compared to Asian HCC patients, Caucasian HCC patients with the TP53 mutation had a decreased proportion of infiltrating M2 macrophages and activating natural killer (NK) cells, and an increased proportion of follicular helper T cells. The RB1 mutation was associated with shorter OS (HR, 3.37; 95% CI, 1.73-6.57; P<0.001) in Asian HCC patients, and shorter DFS (HR, 2.11; 95% CI, 1.15-3.88; P=0.017) in Caucasian HCC patients. Asian HCC patients with the RB1 mutation had a decreased proportion of infiltrating CD8 T cells.

Conclusions

The effects of the TP53 and RB1 mutations on survival differ among Asian and Caucasian HCC patients.

Versatile modification of the CRISPR/Cas9 ribonucleoprotein system to facilitate in vivo application

The development of clustered regularly interspaced short palindromic repeats (CRISPR)/CRISPR-associated (Cas) systems has created a tremendous wave that is sweeping the world of genome editing. The ribonucleoprotein (RNP) method has evolved to be the most advantageous form for in vivo application. Modification of the CRISPR/Cas9 RNP method to adapt delivery through a variety of carriers can either directly improve the stability and specificity of the gene-editing tool in vivo or indirectly endow the system with high gene-editing efficiency that induces few off-target mutations through different delivery methods. The exploration of in vivo applications mediated by various delivery methods lays the foundation for genome research and variety improvements, which is especially promising for better in vivo research in the field of translational biomedicine. In this review, we illustrate the modifiable structures of the Cas9 nuclease and single guide RNA (sgRNA), summarize the latest research progress and discuss the feasibility and advantages of various methods. The highlighted results will enhance our knowledge, stimulate extensive research and application of Cas9 and provide alternatives for the development of rational delivery carriers in multiple fields.

Dysregulated expression of claudins in cancer

Claudins are adhesion molecules located at the tight junctions between epithelial cells. A series of studies have now reported aberrant expression of claudin proteins in the context of neoplastic transformation, suggesting its role in tumorigenesis. However, the precise mechanisms are still not well understood. Studies on expression alterations of claudins have revealed a range of outcomes that reflect the complexity of claudins in terms of spatial localization, tumor type and stage of disease. The diverse and dynamic expression patterns of claudins in cancer are tightly controlled by a wide range of regulatory mechanisms, which are commonly modulated by oncogenic signaling pathways. The present review summarizes the recent knowledge describing the dysregulation of claudin expression in cancer and discusses the intrinsic and extrinsic determinants of the context-specific expression patterns of claudins.

frDriver: A Functional Region Driver Identification for Protein Sequence

Identifying cancer drivers is a crucial challenge to explain the underlying mechanisms of cancer development. There are many methods to identify cancer drivers based on the single mutation site or the entire gene. But they ignore a large number of functional elements with medium in size. It is hypothesized that mutations occurring in different regions of the protein sequence have different effects on the progression of cancer. Here, we develop a novel functional region driver(frDriver) identification method based on Bayesian probability and multiple linear regression models to identify protein regions that can regulate gene expression levels and have high functional impact potential. Combining gene expression data and somatic mutation data, with functional impact scores(SIFT, PROVEAN) as a priori knowledge, we identified cancer driver regions that are most accurate in predicting gene expression levels. We evaluated the performance of frDriver on the BRCA and GBM datasets from TCGA. The results showed that frDriver identified known cancer drivers and outperformed the other three state-of-the-art methods(eDriver, ActiveDriver and OncodriveCLUST). In addition, we performed KEGG pathway and GO term enrichment analysis, and the results indicated that the cancer drivers predicted by frDriver were related to processes such as cancer formation and gene regulation.

Identification and Targeting of Mutant Peptide Neoantigens in Cancer Immunotherapy

In recent decades, adoptive cell transfer and checkpoint blockade therapies have revolutionized immunotherapeutic approaches to cancer treatment. Advances in whole exome/genome sequencing and bioinformatic detection of tumour-specific genetic variations and the amino acid sequence alterations they induce have revealed that T cell mediated anti-tumour immunity is substantially directed at mutated peptide sequences, and the identification and therapeutic targeting of patient-specific mutated peptide antigens now represents an exciting and rapidly progressing frontier of personalized medicine in the treatment of cancer. This review outlines the historical identification and validation of mutated peptide neoantigens as a target of the immune system, and the technical development of bioinformatic and experimental strategies for detecting, confirming and prioritizing both patient-specific or "private" and frequently occurring, shared "public" neoantigenic targets. Further, we examine the range of therapeutic modalities that have demonstrated preclinical and clinical anti-tumour efficacy through specifically targeting neoantigens, including adoptive T cell transfer, checkpoint blockade and neoantigen vaccination.

Scientific and clinical implications of genetic and cellular heterogeneity in uveal melanoma

Here, we discuss the presence and roles of heterogeneity in the development of uveal melanoma. Both genetic and cellular heterogeneity are considered, as their presence became undeniable due to single cell approaches that have recently been used in uveal melanoma analysis. However, the presence of precursor clones and immune infiltrate in uveal melanoma have been described as being part of the tumour already decades ago. Since uveal melanoma grow in the corpus vitreous, they present a unique tumour model because every cell present in the tumour tissue is actually part of the tumour and possibly plays a role. For an effective treatment of uveal melanoma metastasis, it should be clear whether precursor clones and normal cells play an active role in progression and metastasis. We propagate analysis of bulk tissue that allows analysis of tumour heterogeneity in a clinical setting.

Origins of nonsense mutations in human tumor suppressor genes

Understanding the origins of mutations in tumor suppressor genes and oncogenes associated with cancers in different tissues is critical to the development of potential prevention strategies. Analysis of >10,000 nonsense mutations in 63 tumor suppressor genes based on the ratio of the number of nonsense mutations per codon type is reported for each gene. The ratio for C•G→T•A nonsense mutations at Arg CGA codons to the number of CGA codons in all cancers is 23 (3088 total nonsense mutations for 134 CGA codons in the 63 suppressor genes). The ratio for this codon, which is attributed to hydrolytic deamination of 5-methylcytosine at CpG sites based on the sequence context, is 6-fold higher than the next highest ratio that involves a C•G→T•A transition at Trp TGG codons. C•G→A•T transversions at Glu, Ser, Tyr, Gly and Cys codons account for 25 % of the total nonsense mutations but the mutation per codon ratio for these codons is 1.0. Analysis of the bases 5' of the mutated CGA codons in the 63 tumor suppressor genes in all cancers shows a preference of 5'-G > C ∼ T ∼ A, which is not indicative of a role for enzymatic deamination by deaminases. Overall C•G→T•A mutations account for 61 % of all of the nonsense mutations in the collection of tumor suppressor genes. It is demonstrated that the ratio of C•G→T•A deamination-associated nonsense mutations at CGA codons (hydrolytic deamination) to the number of frame shift insertion/deletion mutations (i.e., replication based) for 5 major tumor suppressors genes are very similar in 3 different tissues that undergo a wide range of stem cell divisions. Therefore, the frequency of deamination mutations parallels the number of stem cell replications. This may reflect the generation of more solvent accessible single-stranded DNA regions during polymerization that are kinetically more prone to deamination.

Context-Dependent Roles of Claudins in Tumorigenesis

The barrier and fence functions of the claudin protein family are fundamental to tissue integrity and human health. Increasing evidence has linked claudins to signal transduction and tumorigenesis. The expression of claudins is frequently dysregulated in the context of neoplastic transformation. Studies have uncovered that claudins engage in nearly all aspects of tumor biology and steps of tumor development, suggesting their promise as targets for treatment or biomarkers for diagnosis and prognosis. However, claudins can be either tumor promoters or tumor suppressors depending on the context, which emphasizes the importance of taking various factors, including organ type, environmental context and genetic confounders, into account when studying the biological functions and targeting of claudins in cancer. This review discusses the complicated roles and intrinsic and extrinsic determinants of the context-specific effects of claudins in cancer.

The molecular biology of pancreatic adenocarcinoma: translational challenges and clinical perspectives

Pancreatic cancer is an increasingly common cause of cancer mortality with a tight correspondence between disease mortality and incidence. Furthermore, it is usually diagnosed at an advanced stage with a very dismal prognosis. Due to the high heterogeneity, metabolic reprogramming, and dense stromal environment associated with pancreatic cancer, patients benefit little from current conventional therapy. Recent insight into the biology and genetics of pancreatic cancer has supported its molecular classification, thus expanding clinical therapeutic options. In this review, we summarize how the biological features of pancreatic cancer and its metabolic reprogramming as well as the tumor microenvironment regulate its development and progression. We further discuss potential biomarkers for pancreatic cancer diagnosis, prediction, and surveillance based on novel liquid biopsies. We also outline recent advances in defining pancreatic cancer subtypes and subtype-specific therapeutic responses and current preclinical therapeutic models. Finally, we discuss prospects and challenges in the clinical development of pancreatic cancer therapeutics.

SOX9 is associated with advanced T-stages of clinical stage II colon cancer in young Mexican patients

Colorectal cancer (CRC) is one of the most common malignancies worldwide and includes colon cancer (CC) and rectal cancer (RC). Regarding CC, the development of novel molecular biomarkers for the accurate diagnosis and prognosis, as well as the identification of novel targets for therapeutic intervention, are urgently needed. SRY-related high-mobility group box 9 (SOX9), a transcription factor, is involved in development, and has been associated with the progression of human cancer. However, its underlying clinical and functional effects in CRC have not been fully understood. Therefore, the present study aimed to evaluate the clinical and functional relevance of SOX9 expression in CC. The expression of SOX9 in tumor tissues was evaluated in 97 biopsies from Mexican patients with CC with early-stage I and II disease by immunohistochemistry (IHC). In addition, SOX9 silencing in the HCT116 cell line was performed using specific small interfering RNAs, while downregulation efficiency was verified by reverse transcription-quantitative PCR and immunofluorescence. Spheroid-formation assay was carried out using ultra-low attachment plates. The IHC results showed that SOX9 was upregulated in patients with stage II (91%) and advanced T3 stage (67%) CC. Interestingly, higher SOX9 expression was associated with clinical stage, tumor size and tumor location. Furthermore, increased SOX9 expression was found in relapsed cases with local tumors; however, it was not associated with increased survival probability. Additionally, functional analysis indicated that SOX9 silencing significantly attenuated the sphere-formation capability of HCT116 cells. The present study was the first to evaluate the expression levels of SOX9 in Mexican patients diagnosed with early-stage CC. The aforementioned findings indicated that high SOX9 expression could play an important role in tumorigenesis and be associated with advanced T-stages of clinical-stage II patients, but not with relapse-free survival.

Construction and Validation of a Reliable Six-Gene Prognostic Signature Based on the TP53 Alteration for Hepatocellular Carcinoma

BACKGROUND

The high mutation rate of TP53 in hepatocellular carcinoma (HCC) makes it an attractive potential therapeutic target. However, the mechanism by which TP53 mutation affects the prognosis of HCC is not fully understood.

MATERIAL AND APPROACH

This study downloaded a gene expression profile and clinical-related information from The Cancer Genome Atlas (TCGA) database and the international genome consortium (ICGC) database. We used Gene Set Enrichment Analysis (GSEA) to determine the difference in gene expression patterns between HCC samples with wild-type TP53 (n=258) and mutant TP53 (n=116) in the TCGA cohort. We screened prognosis-related genes by univariate Cox regression analysis and Kaplan-Meier (KM) survival analysis. We constructed a six-gene prognostic signature in the TCGA training group (n=184) by Lasso and multivariate Cox regression analysis. To assess the predictive capability and applicability of the signature in HCC, we conducted internal validation, external validation, integrated analysis and subgroup analysis.

RESULTS

A prognostic signature consisting of six genes (EIF2S1, SEC61A1, CDC42EP2, SRM, GRM8, and TBCD) showed good performance in predicting the prognosis of HCC. The area under the curve (AUC) values of the ROC curve of 1-, 2-, and 3-year survival of the model were all greater than 0.7 in each independent cohort (internal testing cohort, n = 181; TCGA cohort, n = 365; ICGC cohort, n = 229; whole cohort, n = 594; subgroup, n = 9). Importantly, by gene set variation analysis (GSVA) and the single sample gene set enrichment analysis (ssGSEA) method, we found three possible causes that may lead to poor prognosis of HCC: high proliferative activity, low metabolic activity and immunosuppression.

CONCLUSION

Our study provides a reliable method for the prognostic risk assessment of HCC and has great potential for clinical transformation.

Frontiers in Bladder Cancer Genomic Research

Most of the etiology studies of bladder cancer focus on genetic changes, mainly including mutation and activation of oncogenes, mutation and inactivation of tumor suppressor genes, and rearrangement or heterozygous deletion of chromosomes. Moreover, bladder cancer is highly heterogeneous mainly due to abnormal changes in the genome and proteome of tumor cells. Surgery is the main treatment for bladder cancer, but because the recurrence rate is high after surgery and most of the muscle-invasive bladder cancer acquires distant metastasis. Therefore, there is a need to combine with chemotherapy to consolidate the treatment effect. However, there are differences in chemosensitivity among patients. In this article, we review the up-to-date genomic researches on bladder cancer occurrence, development, metastasis, and chemosensitivity in patients, in order to provide some theoretical support for the diagnosis and treatment strategy for bladder cancer.

Progression signature underlies clonal evolution and dissemination of multiple myeloma

Clonal evolution drives tumor progression, dissemination, and relapse in multiple myeloma (MM), with most patients dying of relapsed disease. This multistage process requires tumor cells to enter the circulation, extravasate, and colonize distant bone marrow (BM) sites. Here, we developed a fluorescent or DNA-barcode clone-tracking system on MM PrEDiCT (progression through evolution and dissemination of clonal tumor cells) xenograft mouse model to study clonal behavior within the BM microenvironment. We showed that only the few clones that successfully adapt to the BM microenvironment can enter the circulation and colonize distant BM sites. RNA sequencing of primary and distant-site MM tumor cells revealed a progression signature sequentially activated along human MM progression and significantly associated with overall survival when evaluated against patient data sets. A total of 28 genes were then computationally predicted to be master regulators (MRs) of MM progression. HMGA1 and PA2G4 were validated in vivo using CRISPR-Cas9 in the PrEDiCT model and were shown to be significantly depleted in distant BM sites, indicating their role in MM progression and dissemination. Loss of HMGA1 and PA2G4 also compromised the proliferation, migration, and adhesion abilities of MM cells in vitro. Overall, our model successfully recapitulates key characteristics of human MM disease progression and identified potential new therapeutic targets for MM.

Tumor-Associated Macrophages-Implications for Molecular Oncology and Imaging

Tumor-associated macrophages (TAMs) represent the largest group of leukocytes within the tumor microenvironment (TME) of solid tumors and orchestrate the composition of anti- as well as pro-tumorigenic factors. This makes TAMs an excellent target for novel cancer therapies. The plasticity of TAMs resulting in varying membrane receptors and expression of intracellular proteins allow the specific characterization of different subsets of TAMs. Those markers similarly allow tracking of TAMs by different means of molecular imaging. This review aims to provides an overview of the origin of tumor-associated macrophages, their polarization in different subtypes, and how characteristic markers of the subtypes can be used as targets for molecular imaging and theranostic approaches.

Unraveling the genomic landscape of colorectal cancer through mutational signatures

Colorectal cancer, along with most other cancer types, is driven by somatic mutations. Characteristic patterns of somatic mutations, known as mutational signatures, arise as a result of the activities of different mutational processes. Mutational signatures have diverse origins, including exogenous and endogenous sources. In the case of colorectal cancer, the analysis of mutational signatures has elucidated specific signatures for classically associated DNA repair deficiencies, namely mismatch repair (leading to microsatellite instability), base excision repair (due to MUTYH or NTHL1 mutations), and polymerase proofreading (due to POLE and POLD1 exonuclease domain mutations). Additional signatures also play a role in colorectal cancer, including those related to normal aging and those associated with gut microbiota, as well as a number of signatures with unknown etiologies. This chapter provides an overview of the current knowledge of mutational signatures, with a focus on colorectal cancer and on the recently reported signatures in physiologically normal and inflammatory bowel disease-affected somatic colon tissues.

Targeting the tumor mutanome for personalized vaccination therapy

Next generation sequencing enables identification of immunogenic tumor mutations targetable by individualized vaccines. In the B16F10 melanoma system as pre-clinical proof-of-concept model, we found a total of 563 non-synonymous expressed somatic mutations. Of the mutations we tested, one third were immunogenic. Immunization conferred in vivo tumor control, qualifying mutated epitopes as source for effective vaccines.

Biased Influences of Low Tumor Purity on Mutation Detection in Cancer

The non-cancerous components in tumor tissues, e.g., infiltrating stromal cells and immune cells, dilute tumor purity and might confound genomic mutation profile analyses and the identification of pathological biomarkers. It is necessary to systematically evaluate the influence of tumor purity. Here, using public gastric cancer samples from The Cancer Genome Atlas (TCGA), we firstly showed that numbers of mutation, separately called by four algorithms, were significant positively correlated with tumor purities (all p < 0.05, Spearman rank correlation). Similar results were also observed in other nine cancers from TCGA. Notably, the result was further confirmed by six in-house samples from two gastric cancer patients and five in-house samples from two colorectal cancer patients with different tumor purities. Furthermore, the metastasis mechanism of gastric cancer may be incorrectly characterized as numbers of mutation and tumor purities of 248 lymph node metastatic (N + M0) samples were both significantly lower than those of 121 non-metastatic (N0M0) samples (p < 0.05, Wilcoxon rank-sum test). Similar phenomena were also observed that tumor purities could confound the analysis of histological subtypes of cancer and the identification of microsatellite instability status (MSI) in both gastric and colon cancer. Finally, we suggested that the higher tumor purity, such as above 70%, rather than 60%, could be better to meet the requirement of mutation calling. In conclusion, the influence of tumor purity on the genomic mutation profile and pathological analyses should be fully considered in the further study.

Precise design strategies of nanomedicine for improving cancer therapeutic efficacy using subcellular targeting

Therapeutic efficacy against cancer relies heavily on the ability of the therapeutic agents to reach their final targets. The optimal targets of most cancer therapeutic agents are usually biological macromolecules at the subcellular level, which play a key role in carcinogenesis. Therefore, to improve the therapeutic efficiency of drugs, researchers need to focus on delivering not only the therapeutic agents to the target tissues and cells but also the drugs to the relevant subcellular structures. In this review, we discuss the most recent construction strategies and release patterns of various cancer cell subcellular-targeting nanoformulations, aiming at providing guidance in the overall design of precise nanomedicine. Additionally, future challenges and potential perspectives are illustrated in the hope of enhancing anticancer efficacy and accelerating the translational progress of precise nanomedicine.

A compendium of mutational cancer driver genes

A fundamental goal in cancer research is to understand the mechanisms of cell transformation. This is key to developing more efficient cancer detection methods and therapeutic approaches. One milestone towards this objective is the identification of all the genes with mutations capable of driving tumours. Since the 1970s, the list of cancer genes has been growing steadily. Because cancer driver genes are under positive selection in tumorigenesis, their observed patterns of somatic mutations across tumours in a cohort deviate from those expected from neutral mutagenesis. These deviations, which constitute signals of positive selection, may be detected by carefully designed bioinformatics methods, which have become the state of the art in the identification of driver genes. A systematic approach combining several of these signals could lead to a compendium of mutational cancer genes. In this Review, we present the Integrative OncoGenomics (IntOGen) pipeline, an implementation of such an approach to obtain the compendium of mutational cancer drivers. Its application to somatic mutations of more than 28,000 tumours of 66 cancer types reveals 568 cancer genes and points towards their mechanisms of tumorigenesis. The application of this approach to the ever-growing datasets of somatic tumour mutations will support the continuous refinement of our knowledge of the genetic basis of cancer.

Genome-Wide Screen for Context-Dependent Tumor Suppressors Identified Using in Vivo Models for Neoplasia in Drosophila

Genetic approaches in Drosophila have successfully identified many genes involved in regulation of growth control as well as genetic interactions relevant to the initiation and progression of cancer in vivo. Here, we report on large-scale RNAi-based screens to identify potential tumor suppressor genes that interact with known cancer-drivers: the Epidermal Growth Factor Receptor and the Hippo pathway transcriptional cofactor Yorkie. These screens were designed to identify genes whose depletion drove tissue expressing EGFR or Yki from a state of benign overgrowth into neoplastic transformation in vivo. We also report on an independent screen aimed to identify genes whose depletion suppressed formation of neoplastic tumors in an existing EGFR-dependent neoplasia model. Many of the positives identified here are known to be functional in growth control pathways. We also find a number of novel connections to Yki and EGFR driven tissue growth, mostly unique to one of the two. Thus, resources provided here would be useful to all researchers who study negative regulators of growth during development and cancer in the context of activated EGFR and/or Yki and positive regulators of growth in the context of activated EGFR. Resources reported here are available freely for anyone to use.

Progress in Neoantigen Targeted Cancer Immunotherapies

Immunotherapies that harness the immune system to kill cancer cells have showed significant therapeutic efficacy in many human malignancies. A growing number of studies have highlighted the relevance of neoantigens in recognizing cancer cells by intrinsic T cells. Cancer neoantigens are a direct consequence of somatic mutations presenting on the surface of individual cancer cells. Neoantigens are fully cancer-specific and exempt from central tolerance. In addition, neoantigens are important targets for checkpoint blockade therapy. Recently, technological innovations have made neoantigen discovery possible in a variety of malignancies, thus providing an impetus to develop novel immunotherapies that selectively enhance T cell reactivity for the destruction of cancer cells while leaving normal tissues unharmed. In this review, we aim to introduce the methods of the identification of neoantigens, the mutational patterns of human cancers, related clinical trials, neoantigen burden and sensitivity to immune checkpoint blockade. Moreover, we focus on relevant challenges of targeting neoantigens for cancer treatment.

Approaches for the identification of driver mutations in cancer: A tutorial from a computational perspective

Cancer is a complex disease caused by the accumulation of genetic alterations during the individual's life. Such alterations are called genetic mutations and can be divided into two groups: (1) Passenger mutations, which are not responsible for cancer and (2) Driver mutations, which are significant for cancer and responsible for its initiation and progression. Cancer cells undergo a large number of mutations, of which most are passengers, and few are drivers. The identification of driver mutations is a key point and one of the biggest challenges in Cancer Genomics. Many computational methods for such a purpose have been developed in Cancer Bioinformatics. Such computational methods are complex and are usually described in a high level of abstraction. This tutorial details some classical computational methods, from a computational perspective, with the transcription in an algorithmic format towards an easy access by researchers.

A frequent somatic mutation in the 3'UTR of GAPDH facilitates the development of ovarian cancer by creating a miR‑125b binding site

Ovarian cancer (OVCA) is one of the most common types of cancer in women worldwide. Recent studies have focused on the presence and effect of somatic mutations in patients with OVCA; however, studies on the roles of mutations located in the untranslated regions (UTR) of genes in OVCA remain limited. In the present study, a frequent somatic mutation in the glyceraldehyde 3-phosphate dehydrogenase (GADPH) 3′UTR was identified using transcriptome sequencing of 120 pairs of OVCA tissue samples. The mutant GAPDH 3′UTR promoted tumor growth and cell motility. Furthermore, the mutation in the GAPDH 3′UTR significantly downregulated the levels of mature miR-125b by creating a new miR-125b binding site. Finally, STAT3 levels were increased in SKOV3 cells stably expressing the mutant GADPH 3′UTR, which is a critical target gene of miR-125b. In conclusion, the present study demonstrated that the mutation located in GAPDH 3′UTR promoted OVCA growth and development by sponging miR-125b and thereby affecting STAT3 expression levels.

Tumor evolution in epidermal growth factor receptor mutated non-small cell lung cancer

As the incidence of cancer increases worldwide there is an unmet need to understand cancer evolution to improve patient outcomes. Our growing knowledge of cancer cells' clonal expansion, heterogeneity, adaptation, and relationships within the tumor immune compartment and with the tumor microenvironment has made clear that cancer is a disease that benefits from heterogeneity and evolution. This review outlines recent knowledge of non-small cell lung cancer (NSCLC) pathogenesis and tumor progression from an evolutionary standpoint, focused on the role of oncogenic driver mutations as epidermal growth factor receptor (EGFR). Understanding lung cancer evolution during tumor development, growth, and under treatment pressures is crucial to improve therapeutic interventions and patient outcomes.

Germline and Somatic BRCA1/2 Mutations in 172 Chinese Women With Epithelial Ovarian Cancer

Objective: Despite several nationwide cohort studies of germline BRCA1/2 mutations and several small cohort studies of somatic BRCA1/2 mutations in Chinese epithelial ovarian cancer (EOC) patients, little is known about the impact of these findings on survival outcomes in this population. In this study of 172 retrospectively recruited Chinese EOC patients, germline and somatic BRCA1/2 mutations and their value for predicting survival outcomes were evaluated.

Methods: Unselected patients who visited the study center from January 1, 2011, to January 1, 2015, were recruited and asked to provide peripheral blood samples for this study if they were pathologically confirmed to have primary EOC. All patients received staging surgeries or debulking surgeries involving systemic platinum-based chemotherapy, and the patients were then followed up to December 1, 2017. DNA was extracted from formalin-fixed, paraffin-embedded (FFPE) sections and peripheral blood and sequenced for somatic and germline testing, respectively. The demographic and clinicopathological characteristics of the patients were collected to analyze the distribution of BRCA mutations in subgroups. Survival outcomes were compared among various BRCA mutation statuses using univariate and multivariate models.

Results: In 58 (33.7%) patients, 63 variants were identified, including variants of unknown significance (VUS) in 18 patients (10.5%) and pathogenic or likely pathogenic variants in a partially overlapping set of 41 patients (23.8%). Germline BRCA mutations, somatic BRCA mutations, BRCA1 mutations in general, and BRCA2 mutations in general were found in 35 (20.3%), 7 (4.1%), 28 (16.3%), and 13 (7.6%) patients, respectively. Five recurrent mutations were identified. Personal and family cancer histories as well as hereditary breast and ovarian cancer (HBOC) criteria were associated with deleterious BRCA mutations both overall and in the germline specifically, whereas only age at diagnosis of EOC was associated with somatic BRCA mutations. In univariate and Cox regression analyses, patients with BRCA1/2 mutations in general had significant improvements in progression-free survival (PFS) and overall survival (OS).

Conclusions: In Chinese EOC patients, the distributions and risk factors associated with germline and somatic BRCA1/2 mutations were similar to those previously reported in international studies. Deleterious BRCA mutations in general were associated with improved survival outcomes in this cohort.

Single-cell analysis of structural variations and complex rearrangements with tri-channel processing

Structural variation (SV), involving deletions, duplications, inversions and translocations of DNA segments, is a major source of genetic variability in somatic cells and can dysregulate cancer-related pathways. However, discovering somatic SVs in single cells has been challenging, with copy-number-neutral and complex variants typically escaping detection. Here we describe single-cell tri-channel processing (scTRIP), a computational framework that integrates read depth, template strand and haplotype phase to comprehensively discover SVs in individual cells. We surveyed SV landscapes of 565 single cells, including transformed epithelial cells and patient-derived leukemic samples, to discover abundant SV classes, including inversions, translocations and complex DNA rearrangements. Analysis of the leukemic samples revealed four times more somatic SVs than cytogenetic karyotyping, submicroscopic copy-number alterations, oncogenic copy-neutral rearrangements and a subclonal chromothripsis event. Advancing current methods, single-cell tri-channel processing can directly measure SV mutational processes in individual cells, such as breakage-fusion-bridge cycles, facilitating studies of clonal evolution, genetic mosaicism and SV formation mechanisms, which could improve disease classification for precision medicine.

Directly targeting glutathione peroxidase 4 may be more effective than disrupting glutathione on ferroptosis-based cancer therapy

BACKGROUND

Cancer is one of the major threats to human health and current cancer therapies have been unsuccessful in eradicating it. Ferroptosis is characterized by iron-dependence and lipid hydroperoxides accumulation, and its primary mechanism involves the suppression of system X_c^--GSH (glutathione)-GPX4 (glutathione peroxidase 4) axis. Co-incidentally, cancer cells are also metabolically characterized by iron addiction and ROS tolerance, which makes them vulnerable to ferroptosis. This may provide a new tactic for cancer therapy.

SCOPE OF REVIEW

The general features and mechanisms of ferroptosis, and the basis that makes cancer cells vulnerable to ferroptosis are described. Further, we emphatically discussed that disrupting GSH may not be ideal for triggering ferroptosis of cancer cells in vivo, but directly inhibiting GPX4 and its compensatory members could be more effective. Finally, the various approaches to directly inhibit GPX4 without disturbing GSH were described.

MAJOR CONCLUSIONS

Targeting system X_c^- or GSH may not effectively trigger cancer cells' ferroptosis in vivo the existence of other compensatory pathways. However, directly targeting GPX4 and its compensatory members without disrupting GSH may be more effective to induce ferroptosis in cancer cells in vivo, as GPX4 is essential in preventing ferroptosis.

GENERAL SIGNIFICANCE

Cancer is a severe threat to human health. Ferroptosis-based cancer therapy strategies are promising, but how to effectively induce ferroptosis in cancer cells in vivo is still a question without clear answers. Thus, the viewpoints raised in this review may provide some references and different perspectives for researchers working on ferroptosis-based cancer therapy.

Latency and interval therapy affect the evolution in metastatic colorectal cancer

While comparison of primary tumor and metastases has highlighted genomic heterogeneity in colorectal cancer (CRC), previous studies have focused on a single metastatic site or limited genomic testing. Combining data from whole exome and ultra-deep targeted sequencing, we explored possible evolutionary trajectories beyond the status of these mutations, particularly among patient-matched metastatic tumors. Our findings confirm the persistence of known clinically-relevant mutations (e.g., those of RAS family of oncogenes) in CRC primary and metastases, yet reveal that latency and interval systemic therapy affect the course of evolutionary events within metastatic lesions. Specifically, our analysis of patient-matched primary and multiple metastatic lesions, developed over time, showed a similar genetic composition for liver metastatic tumors, which were 21-months apart. This genetic makeup was different from those identified in lung metastases developed before manifestation of the second liver metastasis. These results underscore the role of latency in the evolutionary path of metastatic CRC and may have implications for future treatment options.

Roles of TrkC Signaling in the Regulation of Tumorigenicity and Metastasis of Cancer

Tropomyosin receptor kinase (Trk) C contributes to the clinicopathology of a variety of human cancers, and new chimeric oncoproteins containing the tyrosine kinase domain of TrkC occur after fusion to the partner genes. Overexpression of TrkC and TrkC fusion proteins was observed in patients with a variety of cancers, including mesenchymal, hematopoietic, and those of epithelial cell lineage. Both microRNAs (miRNAs) and long non-coding RNAs (lncRNAs) were involved in the regulation of TrkC expression through transcriptional and posttranscriptional alteration. Aberrant activation of TrkC and TrkC fusion proteins markedly induces the epithelial-mesenchymal transition (EMT) program, growth rate, tumorigenic capacity via constitutive activation of Ras-MAP kinase (MAPK), PI3K-AKT, and the JAK2-STAT3 pathway. The clinical trial of TrkC or TrkC fusion-positive cancers with newly developed Trk inhibitors demonstrated that Trk inhibitors were highly effective in inducing tumor regression in patients who do not harbor mutations in the kinase domain. Recently, there has been a progressive accumulation of mutations in TrkC or the TrkC fusion protein detected in the clinic and its related cancer cell lines caused by high-throughput DNA sequencing. Despite given the high overall response rate against Trk or Trk fusion proteins-positive solid tumors, acquired drug resistance was observed in patients with various cancers caused by mutations in the Trk kinase domain. To overcome acquired resistance caused by kinase domain mutation, next-generation Trk inhibitors have been developed, and these inhibitors are currently under investigation in clinical trials.

sv-callers: a highly portable parallel workflow for structural variant detection in whole-genome sequence data

Structural variants (SVs) are an important class of genetic variation implicated in a wide array of genetic diseases including cancer. Despite the advances in whole genome sequencing, comprehensive and accurate detection of SVs in short-read data still poses some practical and computational challenges. We present sv-callers, a highly portable workflow that enables parallel execution of multiple SV detection tools, as well as provide users with example analyses of detected SV callsets in a Jupyter Notebook. This workflow supports easy deployment of software dependencies, configuration and addition of new analysis tools. Moreover, porting it to different computing systems requires minimal effort. Finally, we demonstrate the utility of the workflow by performing both somatic and germline SV analyses on different high-performance computing systems.

An Emerging Model for Cancer Development from a Tumor Microenvironment Perspective in Mice and Humans

In the past, cancer development was studied in terms of genetic mutations acquired in cancer cells at each stage of the development. We present an emerging model for cancer development in which the tumor microenvironment (TME) plays an integral part. In this model, the tumor development is initiated by a slowly growing nearly homogeneous colony of cancer cells that can evade detection by the cell's innate mechanism of immunity such as natural killer (NK) cells (first stage; colonization). Subsequently, the colony develops into a tumor filled with lymphocytes and stromal cells, releasing pro-inflammatory cytokines, growth factors, and chemokines (second stage; lymphocyte infiltration). Cancer progression proceeds to a well-vesiculated silent tumor releasing no inflammatory signal, being nearly devoid of lymphocytes (third stage; silenced). Eventually some cancer cells within a tumor undertake epithelial-to-mesenchymal transition (EMT), which leads to cancer metastasis (fourth stage; EMT). If a circulating metastasized cancer cell finds a niche in a new tissue and evades detection by NK cells, it can establish a new colony in which very few stromal cells are present (fifth stage; metastasis), which is much like a colony at the first stage of development. At every stage, cancer cells influence their own TME, and in turn, the TME influences the cancer cells contained within, either by direct interaction between cancer cells and stromal cells or through exchange of cytokines. In this article, we examine clinical findings and animal experiments pertaining to this paradigm-shifting model and consider if, indeed, some aspects of cancer development are governed solely by the TME.

Strategies for nonviral nanoparticle-based delivery of CRISPR/Cas9 therapeutics

CRISPR-based genome editing technology has become an important potential therapeutic tool for various diseases. A vital challenge is to reach a safe, efficient, and clinically suitable delivery of a CRISPR-associated protein and a single-guide RNA. A possible translational approach to applying CRISPR-based technology is the use of viral vectors such as adeno-associated virus. However, such vectors give long-term exposure in vivo that may increase potential off-target effects as well as the risk of immunogenicity. Therefore, limitations to clinical applications are addressed using nonviral delivery systems such as nanoparticle-based delivery strategies. Today, the nanoparticle-based delivery approach is becoming more and more attractive in gene therapeutics because of its specific targeting, scale-up efficiency, efficacy of customization, minor stimulation of immune response, and minimal exposure to nucleases. In this review, we will present the most recent advances in developing innovations and potential advantages of the nanoparticle delivery system in CRISPR genome editing. We will also propose potential strategies of CRISPR-based technology for therapeutic and industrial applications. Our review will differ in focus from previous reviews and advance the literature on the subject by (a) focusing on the challenges of the CRISPR/Cas9 delivery system; (b) focusing on the application of nanoparticle-based delivery of CRISPR components (Cas9 and sgRNA), such as lipids and polymeric vectors; (c) discussing the potential nanoparticle-based delivery approaches for CRISPR/Cas9 application. This article is categorized under: Therapeutic Approaches and Drug Discovery > Emerging Technologies Nanotechnology Approaches to Biology > Nanoscale Systems in Biology.

Primer on Hereditary Cancer Predisposition Genes Included Within Somatic Next-Generation Sequencing Panels

PURPOSE

It has been estimated that 5% to 10% of cancers are due to hereditary causes. Recent data sets indicate that the incidence of hereditary cancer may be as high as 17.5% in patients with cancer, and a notable subset is missed if screening is solely by family history and current syndrome-based testing guidelines. Identification of germline variants has implications for both patients and their families. There is currently no comprehensive overview of cancer susceptibility genes or inclusion of these genes in commercially available somatic testing. We aimed to summarize genes linked to hereditary cancer and the somatic and germline panels that include such genes.

METHODS

Germline predisposition genes were chosen if commercially available for testing. Penetrance was defined as low, moderate, or high according to whether the gene conferred a 0% to 20%, 20% to 50%, or 50% to 100% lifetime risk of developing the cancer or, when percentages were not available, was estimated on the basis of existing literature descriptions.

RESULTS

We identified a total of 89 genes linked to hereditary cancer predisposition, and we summarized these genes alphabetically and by organ system. We considered four germline and six somatic commercially available panel tests and quantified the coverage of germline genes across them. Comparison between the number of genes that had germline importance and the number of genes included in somatic testing showed that many but not all germline genes are tested by frequently used somatic panels.

CONCLUSION

The inclusion of cancer-predisposing genes in somatic variant testing panels makes incidental germline findings likely. Although somatic testing can be used to screen for germline variants, this strategy is inadequate for comprehensive screening. Access to genetic counseling is essential for interpretation of germline implications of somatic testing and implementation of appropriate screening and follow-up.

High Somatic Mutation and Neoantigen Burden Do Not Correlate with Decreased Progression-Free Survival in HCC Patients not Undergoing Immunotherapy

Cancer genome instability leads to accumulation of mutations which may result into tumor-specific mutated "neoantigens", not be affected by central T-cell tolerance. Such neoantigens are considered the optimal target for the patient's anti-tumor T cell immunity as well as for personalized cancer immunotherapy strategies. However, only a minor fraction of predicted neoantigens are relevant to the clinical outcome. In the present study, a prediction algorithm was applied using datasets of RNA sequencing from all 377 Hepatocellular carcinoma (HCC) patients available at The Cancer Genome Atlas (TCGA), to predict neoantigens to be presented by each patient's autologous HLA molecules. Correlation with patients' survival was performed on the 115 samples for whom the exact date of death was known. A total of 30 samples were used for the training set, and 85 samples were used for the validation sets. Neither the somatic mutations nor the number nor the quality of the predicted neoantigens correlate as single parameter with survival of HCC patients who do not undergo immunotherapy treatment. Furthermore, the preferential presentation of such neoantigens in the context of one of the major histocompatibility complex MHC class I molecules does not have an impact on the survival. On the contrary, the expression of Granzyme A (GZMA) is significantly correlated with survival and, in the context of high GZMA, a direct correlation between number and quality of neoantigens with survival is observed. This is in striking contrast to results described in cancer patients undergoing immunotherapy, in which a strong correlation between Tumor Mutational Burden (TMB), number of predicted neoantigens and survival has been reported.

Evolution and Impact of Subclonal Mutations in Papillary Thyroid Cancer

Unlike many cancers, the pattern of tumor evolution in papillary thyroid cancer (PTC) and its potential role in relapse have not been elucidated. In this study, multi-region whole-exome sequencing (WES) was performed on early-stage PTC tumors (n = 257 tumor regions) from 79 individuals, including 17 who had developed relapse, to understand the temporal and spatial framework within which subclonal mutations catalyze tumor evolution and its potential clinical relevance. Paired primary-relapse tumor tissues were also available for a subset of individuals. The resulting catalog of variants was analyzed to explore evolutionary histories, define clonal and subclonal events, and assess the relationship between intra-tumor heterogeneity and relapse-free survival. The multi-region WES approach was key in correctly classifying subclonal mutations, 40% of which would have otherwise been erroneously considered clonal. We observed both linear and branching evolution patterns in our PTC cohort. A higher burden of subclonal mutations was significantly associated with increased risk of relapse. We conclude that relapse in PTC, while generally rare, does not follow a predictable evolutionary path and that subclonal mutation burden may serve as a prognostic factor. Larger studies utilizing multi-region sequencing in relapsed PTC case subjects with matching primary tissues are needed to confirm these observations.

DMCM: a Data-adaptive Mutation Clustering Method to identify cancer-related mutation clusters

Motivation

Functional somatic mutations within coding amino acid sequences confer growth advantage in pathogenic process. Most existing methods for identifying cancer-related mutations focus on the single amino acid or the entire gene level. However, gain-of-function mutations often cluster in specific protein regions instead of existing independently in the amino acid sequences. Some approaches for identifying mutation clusters with mutation density on amino acid chain have been proposed recently. But their performance in identification of mutation clusters remains to be improved.

Results

Here we present a Data-adaptive Mutation Clustering Method (DMCM), in which kernel density estimate (KDE) with a data-adaptive bandwidth is applied to estimate the mutation density, to find variable clusters with different lengths on amino acid sequences. We apply this approach in the mutation data of 571 genes in over twenty cancer types from The Cancer Genome Atlas (TCGA). We compare the DMCM with M2C, OncodriveCLUST and Pfam Domain and find that DMCM tends to identify more significant clusters. The cross-validation analysis shows DMCM is robust and cluster cancer type enrichment analysis shows that specific cancer types are enriched for specific mutation clusters.

Availability and implementation

DMCM is written in Python and analysis methods of DMCM are written in R. They are all released online, available through https://github.com/XinguoLu/DMCM.

Supplementary information

Supplementary data are available at Bioinformatics online.

Discovering novel mutation signatures by latent Dirichlet allocation with variational Bayes inference

MOTIVATION

A cancer genome includes many mutations derived from various mutagens and mutational processes, leading to specific mutation patterns. It is known that each mutational process leads to characteristic mutations, and when a mutational process has preferences for mutations, this situation is called a 'mutation signature.' Identification of mutation signatures is an important task for elucidation of carcinogenic mechanisms. In previous studies, analyses with statistical approaches (e.g. non-negative matrix factorization and latent Dirichlet allocation) revealed a number of mutation signatures. Nonetheless, strictly speaking, these existing approaches employ an ad hoc method or incorrect approximation to estimate the number of mutation signatures, and the whole picture of mutation signatures is unclear.

RESULTS

In this study, we present a novel method for estimating the number of mutation signatures-latent Dirichlet allocation with variational Bayes inference (VB-LDA)-where variational lower bounds are utilized for finding a plausible number of mutation patterns. In addition, we performed cluster analyses for estimated mutation signatures to extract novel mutation signatures that appear in multiple primary lesions. In a simulation with artificial data, we confirmed that our method estimated the correct number of mutation signatures. Furthermore, applying our method in combination with clustering procedures for real mutation data revealed many interesting mutation signatures that have not been previously reported.

AVAILABILITY AND IMPLEMENTATION

All the predicted mutation signatures with clustering results are freely available at http://www.f.waseda.jp/mhamada/MS/index.html. All the C++ source code and python scripts utilized in this study can be downloaded on the Internet (https://github.com/qkirikigaku/MS_LDA).

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Chronic obstructive pulmonary disease (COPD) and lung cancer: common pathways for pathogenesis

Chronic obstructive pulmonary disease (COPD) and lung cancer comprise the leading causes of lung disease-related mortality worldwide. Exposure to tobacco smoke is a mutual aetiology underlying the two diseases, accounting for almost 90% of cases. There is accumulating evidence supporting the role of immune dysfunction, the lung microbiome, extracellular vesicles and underlying genetic susceptibility in the development of COPD and lung cancer. Further, epigenetic factors, involving DNA methylation and microRNA expression, have been implicated in both diseases. Chronic inflammation is a key feature of COPD and could be a potential driver of lung cancer development. Using next generation technologies, further studies investigating the genomics, epigenetics and gene-environment interaction in key molecular pathways will continue to elucidate the pathogenic mechanisms underlying the development of COPD and lung cancer, and contribute to the development of novel diagnostic and prognostic tools for early intervention and personalised therapeutic strategies.

MicroRNAs in Drosophila Cancer Models

MiRNAs are post-transcriptional regulators of gene expression which have been implicated in virtually all biological processes. MiRNAs are frequently dysregulated in human cancers. However, the functional consequences of aberrant miRNA levels are not well understood. Drosophila is emerging as an important in vivo tumor model, especially in the identification of novel cancer genes. Here, we review Drosophila studies which functionally dissect the roles of miRNAs in tumorigenesis. Ultimately, these advances help to understand the implications of miRNA dysregulation in human cancers.

Germline and somatic mutations of multi-gene panel in Chinese patients with epithelial ovarian cancer: a prospective cohort study

Background

Multiple targeted gene sequencing is seldom performed in both germline and somatic testing for ovarian cancer. This study is to evaluate the specific genetic alterations, including both somatic and germline mutations, in Chinese patients with epithelial ovarian cancer (EOC) in a prospective cohort study.

Materials and methods

Mutations in a customed 21-gene panel that included BRCA1, BRCA2, and 19 other tumor suppressor genes related to homologous recombination (HR) deficiency or non-HR deficiency were detected by targeted exon capture and next-generation sequencing (NGS) technology across all coding exons and exon-intron (±20 base pairs) boundaries. Patients were enrolled consecutively and unselectively without age or family history consideration. Sixty-two unselected patients with epithelial ovarian cancer were enrolled in our study to be tested for paired somatic and germline mutations. All patients were tested using a 21-gene panel that included BRCA1, BRCA2, CHEK2, PALB2, BRIP1, TP53, PTEN, STK11, CDH1, ATM, BARD1, MLH1, MRE11A, MSH2, MSH6, MUTYH, NBN, PMS1, PMS2, RAD50, and RAD51C.

Results

Mutation analysis revealed that 77.4% (48/62) of patients carried one or more of 64 identified genetic alterations, including 19 germline and 45 somatic deleterious mutations. Twelve individuals shared both germline and somatic mutations. BRCA mutants existed in 17 of 62 (27.4%) patients. Of the 64 mutations detected, 46 (74.2%) were in 7 other HR or non-HR genes, including TP53, PTEN, ATM, CHEK2, PALB2, RAD51C, and STK11. In somatic mutation analysis, TP53 showed frequent pathogenic or likely pathogenic mutations in 56.5% (35/62) of enrolled cases, among which six cases harbored a loss of heterozygosity.

Conclusions

This is the first report of multi-gene panel testing for germline and somatic mutations among Chinese EOC patients, which revealed a broader deleterious variants than only BRCA testing.

Registration

Registration No. NCT03015376, clinicaltrials.gov, registered on January 10, 2017.

Electronic supplementary material

The online version of this article (10.1186/s13048-019-0560-y) contains supplementary material, which is available to authorized users.

Leveraging protein dynamics to identify cancer mutational hotspots using 3D structures

Large-scale exome sequencing of tumors has enabled the identification of cancer drivers using recurrence-based approaches. Some of these methods also employ 3D protein structures to identify mutational hotspots in cancer-associated genes. In determining such mutational clusters in structures, existing approaches overlook protein dynamics, despite its essential role in protein function. We present a framework to identify cancer driver genes using a dynamics-based search of mutational hotspot communities. Mutations are mapped to protein structures, which are partitioned into distinct residue communities. These communities are identified in a framework where residue-residue contact edges are weighted by correlated motions (as inferred by dynamics-based models). We then search for signals of positive selection among these residue communities to identify putative driver genes, while applying our method to the TCGA (The Cancer Genome Atlas) PanCancer Atlas missense mutation catalog. Overall, we predict 1 or more mutational hotspots within the resolved structures of proteins encoded by 434 genes. These genes were enriched among biological processes associated with tumor progression. Additionally, a comparison between our approach and existing cancer hotspot detection methods using structural data suggests that including protein dynamics significantly increases the sensitivity of driver detection.