Genome-wide analysis of somatic noncoding mutation patterns in cancer

Co-expression in tissue-specific gene networks links genes in cancer-susceptibility loci to known somatic driver genes

BACKGROUND

The genetic background of cancer remains complex and challenging to integrate. Many somatic mutations within genes are known to cause and drive cancer, while genome-wide association studies (GWAS) of cancer have revealed many germline risk factors associated with cancer. However, the overlap between known somatic driver genes and positional candidate genes from GWAS loci is surprisingly small. We hypothesised that genes from multiple independent cancer GWAS loci should show tissue-specific co-regulation patterns that converge on cancer-specific driver genes.

RESULTS

We studied recent well-powered GWAS of breast, prostate, colorectal and skin cancer by estimating co-expression between genes and subsequently prioritising genes that show significant co-expression with genes mapping within susceptibility loci from cancer GWAS. We observed that the prioritised genes were strongly enriched for cancer drivers defined by COSMIC, IntOGen and Dietlein et al. The enrichment of known cancer driver genes was most significant when using co-expression networks derived from non-cancer samples of the relevant tissue of origin.

CONCLUSION

We show how genes within risk loci identified by cancer GWAS can be linked to known cancer driver genes through tissue-specific co-expression networks. This provides an important explanation for why seemingly unrelated sets of genes that harbour either germline risk factors or somatic mutations can eventually cause the same type of disease.

Implications of noncoding regulatory functions in the development of insulinomas

Insulinomas are rare neuroendocrine tumors arising from pancreatic β cells, characterized by aberrant proliferation and altered insulin secretion, leading to glucose homeostasis failure. With the aim of uncovering the role of noncoding regulatory regions and their aberrations in the development of these tumors, we coupled epigenetic and transcriptome profiling with whole-genome sequencing. As a result, we unraveled somatic mutations associated with changes in regulatory functions. Critically, these regions impact insulin secretion, tumor development, and epigenetic modifying genes, including polycomb complex components. Chromatin remodeling is apparent in insulinoma-selective domains shared across patients, containing a specific set of regulatory sequences dominated by the SOX17 binding motif. Moreover, many of these regions are H3K27me3 repressed in β cells, suggesting that tumoral transition involves derepression of polycomb-targeted domains. Our work provides a compendium of aberrant cis-regulatory elements affecting the function and fate of β cells in their progression to insulinomas and a framework to identify coding and noncoding driver mutations.

Diabetes Driven Oncogenesis and Anticancer Potential of Repurposed Antidiabetic Drug: A Systemic Review

Diabetes and cancer are two prevalent disorders, pose significant public health challenges and contribute substantially to global mortality rates, with solely 10 million reported cancer-related deaths in 2020. This review explores the pathological association between diabetes and diverse cancer progressions, examining molecular mechanisms and potential therapeutic intersections. From altered metabolic landscapes to dysregulated signaling pathways, the intricate links are delineated, offering a comprehensive understanding of diabetes as a modulator of tumorigenesis. Cancer cells develop drug resistance through mechanisms like enhanced drug efflux, genetic mutations, and altered drug metabolism, allowing them to survive despite chemotherapeutic agent. Glucose emerges as a pivotal player in diabetes progression, and serving as a crucial energy source for cancer cells, supporting their biosynthetic needs and adaptation to diverse microenvironments. Glycation, a non-enzymatic process that produces advanced glycation end products (AGEs), has been linked to the etiology of cancer and has been shown in a number of tumor forms, such as leiomyosarcomas, adenocarcinomas, and squamous cell carcinomas. Furthermore, in aggressive and metastatic breast cancer, the receptor for AGEs (RAGE) is increased, which may increase the malignancy of the tumor. Reprogramming glucose metabolism manifests as hallmark cancer features, including accelerated cell proliferation, angiogenesis, metastasis, and evasion of apoptosis. This manuscript encapsulates the dual narrative of diabetes as a driver of cancer progression and the potential of repurposed antidiabetic drugs as formidable countermeasures. The amalgamation of mechanistic understanding and clinical trial outcomes establishes a robust foundation for further translational research and therapeutic advancements in the dynamic intersection of diabetes and cancer.

Passive Smoking-Induced Mutagenesis as a Promoter of Lung Carcinogenesis

INTRODUCTION

The International Agency for Research on Cancer has classified passive smoking (PS) or secondhand smoke exposure as a group 1 carcinogen linked to lung cancer. However, in contrast to active smoking, the mutagenic properties of PS remain unclear.

METHODS

A consecutive cohort of 564 lung adenocarcinoma samples from female never-smokers, who provided detailed information about their exposure to PS during adolescence and in their thirties through a questionnaire, was prepared. Of these, all 291 cases for whom frozen tumor tissues were available were subjected to whole exome sequencing to estimate tumor mutational burden, and the top 84 cases who were exposed daily, or not, to PS during adolescence, in their thirties or in both periods, were further subjected to whole genome sequencing.

RESULTS

A modest yet statistically significant increase in tumor mutational burden was observed in the group exposed to PS compared with the group not exposed to PS (median values = 1.44 versus 1.29 per megabase, respectively; p = 0.020). Instead of inducing driver oncogene mutations, PS-induced substantial subclonal mutations exhibiting APOBEC-type signatures, including SMAD4 and ADGRG6 hotspot mutations. A polymorphic APOBEC3A/3B allele-specific to the Asian population that leads to up-regulated expression of APOBEC3A accentuated the mutational load in individuals exposed daily to PS during adolescence.

CONCLUSIONS

This study reveals that PS-induced mutagenesis can promote lung carcinogenesis. The APOBEC3A/3B polymorphism may serve as a biomarker for identifying passive nonsmoking individuals at high risk of developing lung cancer.

Advances in computational and experimental approaches for deciphering transcriptional regulatory networks: Understanding the roles of cis-regulatory elements is essential, and recent research utilizing MPRAs, STARR-seq, CRISPR-Cas9, and machine learning has yielded valuable insights

Understanding the influence of cis-regulatory elements on gene regulation poses numerous challenges given complexities stemming from variations in transcription factor (TF) binding, chromatin accessibility, structural constraints, and cell-type differences. This review discusses the role of gene regulatory networks in enhancing understanding of transcriptional regulation and covers construction methods ranging from expression-based approaches to supervised machine learning. Additionally, key experimental methods, including MPRAs and CRISPR-Cas9-based screening, which have significantly contributed to understanding TF binding preferences and cis-regulatory element functions, are explored. Lastly, the potential of machine learning and artificial intelligence to unravel cis-regulatory logic is analyzed. These computational advances have far-reaching implications for precision medicine, therapeutic target discovery, and the study of genetic variations in health and disease.

Hidden secrets of the cancer genome: unlocking the impact of non-coding mutations in gene regulatory elements

Discoveries in the field of genomics have revealed that non-coding genomic regions are not merely "junk DNA", but rather comprise critical elements involved in gene expression. These gene regulatory elements (GREs) include enhancers, insulators, silencers, and gene promoters. Notably, new evidence shows how mutations within these regions substantially influence gene expression programs, especially in the context of cancer. Advances in high-throughput sequencing technologies have accelerated the identification of somatic and germline single nucleotide mutations in non-coding genomic regions. This review provides an overview of somatic and germline non-coding single nucleotide alterations affecting transcription factor binding sites in GREs, specifically involved in cancer biology. It also summarizes the technologies available for exploring GREs and the challenges associated with studying and characterizing non-coding single nucleotide mutations. Understanding the role of GRE alterations in cancer is essential for improving diagnostic and prognostic capabilities in the precision medicine era, leading to enhanced patient-centered clinical outcomes.

Upstream open reading frames: new players in the landscape of cancer gene regulation

The translation of RNA by ribosomes represents a central biological process and one of the most dysregulated processes in cancer. While translation is traditionally thought to occur exclusively in the protein-coding regions of messenger RNAs (mRNAs), recent transcriptome-wide approaches have shown abundant ribosome activity across diverse stretches of RNA transcripts. The most common type of this kind of ribosome activity occurs in gene leader sequences, also known as 5' untranslated regions (UTRs) of the mRNA, that precede the main coding sequence. Translation of these upstream open reading frames (uORFs) is now known to occur in upwards of 25% of all protein-coding genes. With diverse functions from RNA regulation to microprotein generation, uORFs are rapidly igniting a new arena of cancer biology, where they are linked to cancer genetics, cancer signaling, and tumor-immune interactions. This review focuses on the contributions of uORFs and their associated 5'UTR sequences to cancer biology.

Association of the COL4A2 Gene Polymorphisms with Primary Intracerebral Hemorrhage Risk and Outcome in Chinese Han Population

The relationship of single nucleotide polymorphisms (SNPs) in COL4A2 gene with risk and outcome of primary intracerebral hemorrhage (ICH) in the Chinese Han population remains unclear, which was investigated in this study. Primary ICH patients and non-stroke controls of Chinese Han ethnicity were enrolled. The genotypes of 8 tag-SNPs were determined using a custom-by-design 48-Plex SNPscan Kit. Poor 3-month outcome was defined as modified Rankin Scale score 4-6. Logistic regression was employed to examine association between COL4A2 variants and risk and poor outcome of primary ICH. 323 patients with primary ICH and 376 stroke-free controls were included. Compared to controls, the rs1049931 G and rs1049906 C alleles were associated with increased ICH risk (p = 0.027 and 0.033), and these two allele counts increased this risk after adjustments respectively (additive model: adjusted OR [aOR] 1.41, 95% CI 1.03-1.94, corrected p = 0.043; aOR 1.37, 95% CI 1.01-1.86, corrected p = 0.043). The rs1049931 AG/GG and rs1049906 CT/CC genotypes showed increased susceptibility to non-lobar hemorrhage (aOR 1.63, 95% CI 1.06-2.50, p = 0.025; aOR 1.63, 95% CI 1.07-2.47, p = 0.022). Haplotype analysis revealed an association between rs1049906-rs1049931 haplotype CG and ICH risk (OR 1.36, 95% CI 1.05-1.78, p = 0.021). Regarding clinical outcome, the rs3803230 C allele (dominant model: aOR 1.94, 95% CI 1.04-3.63, p = 0.037) and haplotype AC of rs7990214-rs3803230 (OR 1.98, 95% CI 1.13-3.46, p = 0.015) contributed to 3-month poor outcome. The COL4A2 polymorphisms are associated with an increased risk of primary ICH, mainly non-lobar hemorrhage, and with long-term poor outcome after ICH in Chinese Han population.

Tissue-specific enhancer-gene maps from multimodal single-cell data identify causal disease alleles

Translating genome-wide association study (GWAS) loci into causal variants and genes requires accurate cell-type-specific enhancer-gene maps from disease-relevant tissues. Building enhancer-gene maps is essential but challenging with current experimental methods in primary human tissues. Here we developed a nonparametric statistical method, SCENT (single-cell enhancer target gene mapping), that models association between enhancer chromatin accessibility and gene expression in single-cell or nucleus multimodal RNA sequencing and ATAC sequencing data. We applied SCENT to 9 multimodal datasets including >120,000 single cells or nuclei and created 23 cell-type-specific enhancer-gene maps. These maps were highly enriched for causal variants in expression quantitative loci and GWAS for 1,143 diseases and traits. We identified likely causal genes for both common and rare diseases and linked somatic mutation hotspots to target genes. We demonstrate that application of SCENT to multimodal data from disease-relevant human tissue enables the scalable construction of accurate cell-type-specific enhancer-gene maps, essential for defining noncoding variant function.

Somatic mutations in aging and disease

Time always leaves its mark, and our genome is no exception. Mutations in the genome of somatic cells were first hypothesized to be the cause of aging in the 1950s, shortly after the molecular structure of DNA had been described. Somatic mutation theories of aging are based on the fact that mutations in DNA as the ultimate template for all cellular functions are irreversible. However, it took until the 1990s to develop the methods to test if DNA mutations accumulate with age in different organs and tissues and estimate the severity of the problem. By now, numerous studies have documented the accumulation of somatic mutations with age in normal cells and tissues of mice, humans, and other animals, showing clock-like mutational signatures that provide information on the underlying causes of the mutations. In this review, we will first briefly discuss the recent advances in next-generation sequencing that now allow quantitative analysis of somatic mutations. Second, we will provide evidence that the mutation rate differs between cell types, with a focus on differences between germline and somatic mutation rate. Third, we will discuss somatic mutational signatures as measures of aging, environmental exposure, and activities of DNA repair processes. Fourth, we will explain the concept of clonally amplified somatic mutations, with a focus on clonal hematopoiesis. Fifth, we will briefly discuss somatic mutations in the transcriptome and in our other genome, i.e., the genome of mitochondria. We will end with a brief discussion of a possible causal contribution of somatic mutations to the aging process.

CMC: Cancer miRNA Census - a list of cancer-related miRNA genes

A growing body of evidence indicates an important role of miRNAs in cancer; however, there is no definitive, convenient-to-use list of cancer-related miRNAs or miRNA genes that may serve as a reference for analyses of miRNAs in cancer. To this end, we created a list of 165 cancer-related miRNA genes called the Cancer miRNA Census (CMC). The list is based on a score, built on various types of functional and genetic evidence for the role of particular miRNAs in cancer, e.g. miRNA-cancer associations reported in databases, associations of miRNAs with cancer hallmarks, or signals of positive selection of genetic alterations in cancer. The presence of well-recognized cancer-related miRNA genes, such as MIR21, MIR155, MIR15A, MIR17 or MIRLET7s, at the top of the CMC ranking directly confirms the accuracy and robustness of the list. Additionally, to verify and indicate the reliability of CMC, we performed a validation of criteria used to build CMC, comparison of CMC with various cancer data (publications and databases), and enrichment analyses of biological pathways and processes such as Gene Ontology or DisGeNET. All validation steps showed a strong association of CMC with cancer/cancer-related processes confirming its usefulness as a reference list of miRNA genes associated with cancer.

Cancer Evolution: A Multifaceted Affair

Cancer cells adapt and survive through the acquisition and selection of molecular modifications. This process defines cancer evolution. Building on a theoretical framework based on heritable genetic changes has provided insights into the mechanisms supporting cancer evolution. However, cancer hallmarks also emerge via heritable nongenetic mechanisms, including epigenetic and chromatin topological changes, and interactions between tumor cells and the tumor microenvironment. Recent findings on tumor evolutionary mechanisms draw a multifaceted picture where heterogeneous forces interact and influence each other while shaping tumor progression. A comprehensive characterization of the cancer evolutionary toolkit is required to improve personalized medicine and biomarker discovery.

SIGNIFICANCE

Tumor evolution is fueled by multiple enabling mechanisms. Importantly, genetic instability, epigenetic reprogramming, and interactions with the tumor microenvironment are neither alternative nor independent evolutionary mechanisms. As demonstrated by findings highlighted in this perspective, experimental and theoretical approaches must account for multiple evolutionary mechanisms and their interactions to ultimately understand, predict, and steer tumor evolution.

Rethinking cancer initiation: The role of large-scale mutational events

Cancer initiation is revisited in light of recent discoveries in cancer pathogenesis. Of note is the detection of mutated cancer genes in benign conditions. More significantly, somatic clones, which harbor mutations in cancer genes, arise in normal tissues from early development through adulthood, but seldom do they transform into cancer. Further, clustered mutational events-kataegis, chromothripsis and chromoplexy-are widespread in cancer, generating point mutations and chromosomal rearrangements in a single cellular catastrophe. These observations are contrary to the prevailing somatic mutation theory, which states that a cancer is caused by the gradual accumulation of mutations over time. A different perspective is proposed within the framework of Waddington's epigenetic landscape wherein tumorigenesis is viewed primarily as a disruption of cell development. Cell types are defined by their specific gene-expression profiles, determined by the gene regulatory network, and can be regarded as attractor states of the network dynamics: they represent specific, self-stabilizing patterns of gene activities across the genome. However, large-scale mutational events reshape the landscape topology, creating abnormal "unphysiological" attractors. This is the crux of the process of initiation. Initiation primes the cell for conversion into a tumor phenotype by oncogenes and tumor suppressor genes, which drive cell proliferation and clonal diversification. This view of tumorigenesis calls for a different approach to therapy.

ioSearch: An approach for identifying interacting multiomics biomarkers using a novel algorithm with application on breast cancer data sets

Identification of biomarkers by integrating multiple omics together is important because complex diseases occur due to an intricate interplay of various genetic materials. Traditional single-omics association tests neither explore this crucial interomics dependence nor identify moderately weak signals due to the multiple-testing burden. Conversely, multiomics data integration imparts complementary information but suffers from an increased multiple-testing burden, data diversity inherent with different omics features, high-dimensionality, and so forth. Most of the available methods address subtype classification using dimension-reduction techniques to circumvent the sample size issue but interacting multiomics biomarker identification methods are unavailable. We propose a two-step model that first investigates phenotype-omics association using logistic regression. Then, selects disease-associated omics using sparse principal components which explores the interrelationship of multiple variables from two omics in a multivariate multiple regression framework. On the basis of this model, we developed a multiomics biomarker identification algorithm, interacting omics search (ioSearch), that jointly tests the effect of multiple omics with disease and between-omics associations by using pathway information that subsequently reduces the multiple-testing burden. Further, inference in terms of p values potentially makes it an easily interpretable biomarker identification tool. Extensive simulation demonstrates ioSearch as statistically powerful with a controlled Type-I error rate. Its application to publicly available breast cancer data sets identified relevant omics features in important pathways.

Super-enhancer driven SOX2 promotes tumor formation by chromatin re-organization in nasopharyngeal carcinoma

BACKGROUND

Nasopharyngeal carcinoma (NPC) is a malignant head and neck cancer with a high incidence in Southern China and Southeast Asia. Patients with remote metastasis and recurrent NPC have poor prognosis. Thus, a better understanding of NPC pathogenesis may identify novel therapies to address the unmet clinical needs.

METHODS

H3K27ac ChIP-seq and HiChIP was applied to understand the enhancer landscapes and the chromosome interactions. Whole genome sequencing was conducted to analyze the relationship between genomic variations and epigenetic dysregulation. CRISPRi and JQ1 treatment were used to evaluate the transcriptional regulation of SOX2 SEs. Colony formation assay, survival analysis and in vivo subcutaneous patient-derived xenograft assays were applied to explore the function and clinical relevance of SOX2 in NPC.

FINDINGS

We globally mapped the enhancer landscapes and generated NPC enhancer connectomes, linking NPC specific enhancers and SEs. We found five overlapped genes, including SOX2, among super-enhancer regulated genes, survival related genes and NPC essential genes. The mRNA expression of SOX2 was repressed when applying CRISPRi targeting different SOX2 SEs or JQ1 treatment. Next, we identified a genetic variation (Chr3:181422197, G > A) in SOX2 SE which is correlated with higher expression of SOX2 and poor survival. In addition, SOX2 was highly expressed in NPC and is correlated with short survival in patients with NPC. Knock-down of SOX2 suppressed tumor growth in vitro and in vivo.

INTERPRETATION

Our study demonstrated the super-enhancer landscape with chromosome interactions and identified super-enhancer driven SOX2 promotes tumorigenesis, suggesting that SOX2 is a potential therapeutic target for patients with NPC.

FUNDING

A full list of funding bodies that contributed to this study can be found in the Acknowledgements section.

Identification of a RAD51B enhancer variant for susceptibility and progression to glioma

BACKGROUND

RAD51B plays a significant role in homologous recombination-mediated repair of DNA double-strand breaks. Many enhancer variants are involved in cancer development and progression. However, the significance of enhancer variants of RAD51B in glioma susceptibility and progression remains unclear.

METHODS

A case-control study consisting of 1056 individuals was conducted to evaluate the associations of enhancer variants of RAD51B with glioma susceptibility and progression. Sequenom MassARRAY technology was used for genotyping. The function of enhancer variants was explored by biochemical assays.

RESULTS

A significantly decreased risk of glioma was associated with rs6573816 GC genotype compared with rs6573816 GG genotype (OR = 0.66, 95% CI 0.45-0.97; P = 0.034). Multivariable Cox regression revealed that rs6573816 was significantly associated with glioma progression in a sex-dependent manner. Worse PFS was found in the male patients with high grade glioma carrying rs6573816 GC or CC genotype (HR = 2.28, 95% CI 1.14-4.57; P = 0.020). The rs6573816 C allele repressed enhancer activity by affecting transcription factor POU2F1 binding, which resulted in lower expression of RAD51B. Remarkably attenuated expression of RAD51B was observed following POU2F1 knockdown. Consistently, positive correlation between the expression of POU2F1 and RAD51B was found in lymphoblastic cells and glioma tissues.

CONCLUSIONS

These results indicate that an enhancer variant of RAD51B rs6573816 influences enhancer activity by changing a POU2F1 binding site and confers susceptibility and progression to glioma.

Genome-guided discovery of cancer therapeutic targets

The success of precision oncology-which aims to match the right therapies to the right patients based on molecular status-is predicated on a robust pipeline of molecular targets against which therapies can be developed. Recent advances in genomics and functional genetics have enabled the unbiased discovery of novel molecular targets at scale. We summarize the promise and challenges in integrating genomic and functional genetic landscapes of cancer to establish the next generation of cancer targets.

Methylation across the central dogma in health and diseases: new therapeutic strategies

The proper transfer of genetic information from DNA to RNA to protein is essential for cell-fate control, development, and health. Methylation of DNA, RNAs, histones, and non-histone proteins is a reversible post-synthesis modification that finetunes gene expression and function in diverse physiological processes. Aberrant methylation caused by genetic mutations or environmental stimuli promotes various diseases and accelerates aging, necessitating the development of therapies to correct the disease-driver methylation imbalance. In this Review, we summarize the operating system of methylation across the central dogma, which includes writers, erasers, readers, and reader-independent outputs. We then discuss how dysregulation of the system contributes to neurological disorders, cancer, and aging. Current small-molecule compounds that target the modifiers show modest success in certain cancers. The methylome-wide action and lack of specificity lead to undesirable biological effects and cytotoxicity, limiting their therapeutic application, especially for diseases with a monogenic cause or different directions of methylation changes. Emerging tools capable of site-specific methylation manipulation hold great promise to solve this dilemma. With the refinement of delivery vehicles, these new tools are well positioned to advance the basic research and clinical translation of the methylation field.

Using evolutionary constraint to define novel candidate driver genes in medulloblastoma

Current knowledge of cancer genomics remains biased against noncoding mutations. To systematically search for regulatory noncoding mutations, we assessed mutations in conserved positions in the genome under the assumption that these are more likely to be functional than mutations in positions with low conservation. To this end, we use whole-genome sequencing data from the International Cancer Genome Consortium and combined it with evolutionary constraint inferred from 240 mammals, to identify genes enriched in noncoding constraint mutations (NCCMs), mutations likely to be regulatory in nature. We compare medulloblastoma (MB), which is malignant, to pilocytic astrocytoma (PA), a primarily benign tumor, and find highly different NCCM frequencies between the two, in agreement with the fact that malignant cancers tend to have more mutations. In PA, a high NCCM frequency only affects the BRAF locus, which is the most commonly mutated gene in PA. In contrast, in MB, >500 genes have high levels of NCCMs. Intriguingly, several loci with NCCMs in MB are associated with different ages of onset, such as the HOXB cluster in young MB patients. In adult patients, NCCMs occurred in, e.g., the WASF-2/AHDC1/FGR locus. One of these NCCMs led to increased expression of the SRC kinase FGR and augmented responsiveness of MB cells to dasatinib, a SRC kinase inhibitor. Our analysis thus points to different molecular pathways in different patient groups. These newly identified putative candidate driver mutations may aid in patient stratification in MB and could be valuable for future selection of personalized treatment options.

Regulation of T cell differentiation and function by long noncoding RNAs in homeostasis and cancer

Long noncoding RNAs (lncRNAs) increase in genomes of complex organisms and represent the largest group of RNA genes transcribed in mammalian cells. Previously considered only transcriptional noise, lncRNAs comprise a heterogeneous class of transcripts that are emerging as critical regulators of T cell-mediated immunity. Here we summarize the lncRNA expression landscape of different T cell subsets and highlight recent advances in the role of lncRNAs in regulating T cell differentiation, function and exhaustion during homeostasis and cancer. We discuss the different molecular mechanisms of lncRNAs and highlight lncRNAs that can serve as novel targets to modulate T cell function or to improve the response to cancer immunotherapies by modulating the immunosuppressive tumor microenvironment.

Gain-of-function mutations in the catalytic domain of DOT1L promote lung cancer malignant phenotypes via the MAPK/ERK signaling pathway

Lung cancer is a lethal malignancy lacking effective therapies. Emerging evidence suggests that epigenetic enzyme mutations are closely related to the malignant phenotype of lung cancer. Here, we identified a series of gain-of-function mutations in the histone methyltransferase DOT1L. The strongest of them is R231Q, located in the catalytic DOT domain. R231Q can enhance the substrate binding ability of DOT1L. Moreover, R231Q promotes cell growth and drug resistance of lung cancer cells in vitro and in vivo. Mechanistic studies also revealed that the R231Q mutant specifically activates the MAPK/ERK signaling pathway by enriching H3K79me2 on the RAF1 promoter and epigenetically regulating the expression of downstream targets. The combination of a DOT1L inhibitor (SGC0946) and a MAPK/ERK axis inhibitor (binimetinib) can effectively reverse the R231Q-induced phenomena. Our results reveal gain-of-function mutations in an epigenetic enzyme and provide promising insights for the precise treatment of lung cancer patients.

Integrative identification of non-coding regulatory regions driving metastatic prostate cancer

Large-scale sequencing efforts of thousands of tumor samples have been undertaken to understand the mutational landscape of the coding genome. However, the vast majority of germline and somatic variants occur within non-coding portions of the genome. These genomic regions do not directly encode for specific proteins, but can play key roles in cancer progression, for example by driving aberrant gene expression control. Here, we designed an integrative computational and experimental framework to identify recurrently mutated non-coding regulatory regions that drive tumor progression. Application of this approach to whole-genome sequencing (WGS) data from a large cohort of metastatic castration-resistant prostate cancer (mCRPC) revealed a large set of recurrently mutated regions. We used (i) in silico prioritization of functional non-coding mutations, (ii) massively parallel reporter assays, and (iii) in vivo CRISPR-interference (CRISPRi) screens in xenografted mice to systematically identify and validate driver regulatory regions that drive mCRPC. We discovered that one of these enhancer regions, GH22I030351, acts on a bidirectional promoter to simultaneously modulate expression of U2-associated splicing factor SF3A1 and chromosomal protein CCDC157. We found that both SF3A1 and CCDC157 are promoters of tumor growth in xenograft models of prostate cancer. We nominated a number of transcription factors, including SOX6, to be responsible for higher expression of SF3A1 and CCDC157. Collectively, we have established and confirmed an integrative computational and experimental approach that enables the systematic detection of non-coding regulatory regions that drive the progression of human cancers.

Applications of tissue-specific and cancer-selective gene promoters for cancer diagnosis and therapy

Current treatment of solid tumors with standard of care chemotherapies, radiation therapy and/or immunotherapies are often limited by severe adverse toxic effects, resulting in a narrow therapeutic index. Cancer gene therapy represents a targeted approach that in principle could significantly reduce undesirable side effects in normal tissues while significantly inhibiting tumor growth and progression. To be effective, this strategy requires a clear understanding of the molecular biology of cancer development and evolution and developing biological vectors that can serve as vehicles to target cancer cells. The advent and fine tuning of omics technologies that permit the collective and spatial recognition of genes (genomics), mRNAs (transcriptomics), proteins (proteomics), metabolites (metabolomics), epiomics (epigenomics, epitranscriptomics, and epiproteomics), and their interactomics in defined complex biological samples provide a roadmap for identifying crucial targets of relevance to the cancer paradigm. Combining these strategies with identified genetic elements that control target gene expression uncovers significant opportunities for developing guided gene-based therapeutics for cancer. The purpose of this review is to overview the current state and potential limitations in developing gene promoter-directed targeted expression of key genes and highlights their potential applications in cancer gene therapy.

Clinical implications of lncRNA LINC-PINT in cancer

Long noncoding RNAs (lncRNAs) possess the potential for therapeutic targeting to treat many disorders, including cancers. Several RNA-based therapeutics (ASOs and small interfering RNAs) have gained FDA approval over the past decade. And with their potent effects, lncRNA-based therapeutics are of emerging significance. One important lncRNA target is LINC-PINT, with its universalized functions and relationship with the famous tumor suppressor gene TP53. Establishing clinical relevance, much like p53, the tumor suppressor activity of LINC-PINT is implicated in cancer progression. Moreover, several molecular targets of LINC-PINT are directly or indirectly used in routine clinical practice. We further associate LINC-PINT with immune responses in colon adenocarcinoma, proposing the potential utility of LINC-PINT as a novel biomarker of immune checkpoint inhibitors. Collectively, current evidence suggests LINC-PINT can be considered for use as a diagnostic/prognostic marker for cancer and several other diseases.

Widespread perturbation of ETS factor binding sites in cancer

Although >90% of somatic mutations reside in non-coding regions, few have been reported as cancer drivers. To predict driver non-coding variants (NCVs), we present a transcription factor (TF)-aware burden test based on a model of coherent TF function in promoters. We apply this test to NCVs from the Pan-Cancer Analysis of Whole Genomes cohort and predict 2555 driver NCVs in the promoters of 813 genes across 20 cancer types. These genes are enriched in cancer-related gene ontologies, essential genes, and genes associated with cancer prognosis. We find that 765 candidate driver NCVs alter transcriptional activity, 510 lead to differential binding of TF-cofactor regulatory complexes, and that they primarily impact the binding of ETS factors. Finally, we show that different NCVs within a promoter often affect transcriptional activity through shared mechanisms. Our integrated computational and experimental approach shows that cancer NCVs are widespread and that ETS factors are commonly disrupted.

Hereditable variants of classical protein tyrosine phosphatase genes: Will they prove innocent or guilty?

Protein tyrosine phosphatases, together with protein tyrosine kinases, control many molecular signaling steps that control life at cellular and organismal levels. Impairing alterations in the genes encoding the involved proteins is expected to profoundly affect the quality of life-if compatible with life at all. Here, we review the current knowledge on the effects of germline variants that have been reported for genes encoding a subset of the protein tyrosine phosphatase superfamily; that of the thirty seven classical members. The conclusion must be that the newest genome research tools produced an avalanche of data that suggest 'guilt by association' for individual genes to specific disorders. Future research should face the challenge to investigate these accusations thoroughly and convincingly, to reach a mature genotype-phenotype map for this intriguing protein family.

Zn-Co metal organic frameworks coated with chitosand and Au nanoparticles for chemo-photothermal-targeted combination therapy of liver cancer

The toxic effects of chemotherapy drugs on normal tissues are still a major limiting factor in cancer treatment. In this paper, we report a metal-organic framework (Zn-Co ZIF) with chitosan-coated outer layer as a carrier for the drug adriamycin hydrochloride (DOX), a treatment for liver cancer, as a novel anti-cancer nanodrug-enhanced carrier. Gold nanoparticles, a good photothermal conversion agent, were combined with the target SH-RGD during surface functionalisation to prepare Zn-Co ZIF@DOX-CS-Au-RGD (ZD-CAR), a nanoplatform with good photothermal conversion properties and targeting for combined liver cancer therapy. ZD-CAR was developed after RGD accurately targeted the tumour and entered the tumour microenvironment (TME), it cleaves and releases the liver cancer therapeutic agent (DOX) in a weak acidic environment to effectively kill tumour cells. The metal skeleton cleavage releases Co²⁺, which catalyzes the production of oxygen from H₂O₂ to alleviate the tumour hypoxic environment. The dissolved oxygen could reach 14 mg/L after adding 80 mg/mL of ZD-CAR. Meanwhile, gold nanoparticles could convert light energy into heat energy under 808 NIR irradiation to induce local superheating and kill tumour cells. In summary, this study developed a nanoplatform that combines chemo-photothermal-targeted therapy. It has shown good therapeutic effeciency in cellular experiments and performance tests and has promising applications in anti-cancer therapy.

Efficient Selection of Enhancers and Promoters from MIA PaCa-2 Pancreatic Cancer Cells by ChIP-lentiMPRA

A library of active genome regulatory elements (putative promoters and enhancers) from MIA PaCa-2 pancreatic adenocarcinoma cells was constructed using a specially designed lentiviral vector and a massive parallel reporter assay (ChIP-lentiMPRA). Chromatin immunoprecipitation of the cell genomic DNA by H3K27ac antibodies was used for primary enrichment of the library for regulatory elements. Totally, 11,264 unique genome regions, many of which are capable of enhancing the expression of the CopGFP reporter gene from the minimal CMV promoter, were identified. The regions tend to be located near promoters. Based on the proximity assay, we found an enrichment of highly expressed genes among those associated with three or more mapped distal regions (2 kb distant from the 5'-ends of genes). It was shown significant enrichment of genes related to carcinogenesis or Mia PaCa-2 cell identity genes in this group. In contrast, genes associated with 1-2 distal regions or only with proximal regions (within 2 kbp of the 5'-ends of genes) are more often related to housekeeping functions. Thus, ChIP-lentiMPRA is a useful strategy for creating libraries of regulatory elements for the study of tumor-specific gene transcription.

Multiplexed functional genomic assays to decipher the noncoding genome

Linkage disequilibrium and the incomplete regulatory annotation of the noncoding genome complicates the identification of functional noncoding genetic variants and their causal association with disease. Current computational methods for variant prioritization have limited predictive value, necessitating the application of highly parallelized experimental assays to efficiently identify functional noncoding variation. Here, we summarize two distinct approaches, massively parallel reporter assays and CRISPR-based pooled screens and describe their flexible implementation to characterize human noncoding genetic variation at unprecedented scale. Each approach provides unique advantages and limitations, highlighting the importance of multimodal methodological integration. These multiplexed assays of variant effects are undoubtedly poised to play a key role in the experimental characterization of noncoding genetic risk, informing our understanding of the underlying mechanisms of disease-associated loci and the development of more robust predictive classification algorithms.

Small molecule inhibitors targeting the cancers

Compared with traditional therapies, targeted therapy has merits in selectivity, efficacy, and tolerability. Small molecule inhibitors are one of the primary targeted therapies for cancer. Due to their advantages in a wide range of targets, convenient medication, and the ability to penetrate into the central nervous system, many efforts have been devoted to developing more small molecule inhibitors. To date, 88 small molecule inhibitors have been approved by the United States Food and Drug Administration to treat cancers. Despite remarkable progress, small molecule inhibitors in cancer treatment still face many obstacles, such as low response rate, short duration of response, toxicity, biomarkers, and resistance. To better promote the development of small molecule inhibitors targeting cancers, we comprehensively reviewed small molecule inhibitors involved in all the approved agents and pivotal drug candidates in clinical trials arranged by the signaling pathways and the classification of small molecule inhibitors. We discussed lessons learned from the development of these agents, the proper strategies to overcome resistance arising from different mechanisms, and combination therapies concerned with small molecule inhibitors. Through our review, we hoped to provide insights and perspectives for the research and development of small molecule inhibitors in cancer treatment.

Use of Publication Dynamics to Distinguish Cancer Genes and Bystander Genes

de Magalhães has shown recently that most human genes have several papers in PubMed mentioning cancer, leading the author to suggest that every gene is associated with cancer, a conclusion that contradicts the widely held view that cancer is driven by a limited number of cancer genes, whereas the majority of genes are just bystanders in carcinogenesis. We have analyzed PubMed to decide whether publication metrics supports the distinction of bystander genes and cancer genes. The dynamics of publications on known cancer genes followed a similar pattern: seminal discoveries triggered a burst of cancer-related publications that validated and expanded the discovery, resulting in a rise both in the number and proportion of cancer-related publications on that gene. The dynamics of publications on bystander genes was markedly different. Although there is a slow but continuous time-dependent rise in the proportion of papers mentioning cancer, this phenomenon just reflects the increasing publication bias that favors cancer research. Despite this bias, the proportion of cancer papers on bystander genes remains low. Here, we show that the distinctive publication dynamics of cancer genes and bystander genes may be used for the identification of cancer genes.