Promoter of lncRNA Gene PVT1 Is a Tumor-Suppressor DNA Boundary Element.

Noncoding mutations in cancer genomes are frequent but challenging to interpret. PVT1 encodes an oncogenic lncRNA, but recurrent translocations and deletions in human cancers suggest alternative mechanisms. Here, we show that the PVT1 promoter has a tumor-suppressor function that is independent of PVT1 lncRNA. CRISPR interference of PVT1 promoter enhances breast cancer cell competition and growth in vivo. The promoters of the PVT1 and the MYC oncogenes, located 55 kb apart on chromosome 8q24, compete for engagement with four intragenic enhancers in the PVT1 locus, thereby allowing the PVT1 promoter to regulate pause release of MYC transcription. PVT1 undergoes developmentally regulated monoallelic expression, and the PVT1 promoter inhibits MYC expression only from the same chromosome via promoter competition. Cancer genome sequencing identifies recurrent mutations encompassing the human PVT1 promoter, and genome editing verified that PVT1 promoter mutation promotes cancer cell growth. These results highlight regulatory sequences of lncRNA genes as potential disease-associated DNA elements.

Strontium Ranelate Ameliorates Intervertebral Disc Degeneration via Regulating TGF-ß1/NF-κB Axis.

Intervertebral disc degeneration (IVDD) is a prevalent and debilitating condition characterized by chronic back pain and reduced quality of life. Strontium ranelate (SRR) is a compound traditionally used for treating osteoporosis via activating TGF-ß1 signaling pathway. Recent studies have proved the anti-inflammatory effect of SRR on chondrocytes. Although the exact mechanism of IVDD remains unclear, accumulating evidences have emphasized the involvement of multifactorial pathogenesis including inflammation, oxidative stress damage, and etc. However, the biological effect of SRR on IVDD and its molecular mechanism has not been investigated. Firstly, this study proved the decreased expression of Transforming Growth Factor-beta 1(TGF-ß1) in degenerated human intervertebral disc tissues. Subsequently, we confirmed for the first time that SRR could promote cell proliferation, mitigate inflammation and oxidative stress in human nucleus pulposus cells in vitro via increasing the expression of TGF-ß1 and suppressing the Nuclear Factor Kappa-Light-Chain-Enhancer of Activated B Cells (NF-κB) pathway. The molecular docking result proved the interaction between SRR and TGF-ß1 protein. To further verify this interaction, gain- and loss- of function experiments were conducted. We discovered that both TGF-ß1 knockdown and overexpression influenced the activation of the NF-κB pathway. Taken together, SRR could mitigate IL-1ß induced-cell dysfunction in human nucleus pulposus cells by regulating TGF-ß1/NF-κB axis in vitro. Finally, the in vivo therapeutic effect of SRR on IVDD was confirmed. Our findings may contribute to the understanding of the complex interplay between inflammation and degenerative processes in the intervertebral disc and provide valuable insights into the development of targeted treatment-based therapeutics for IVDD.

Elements and evolutionary determinants of genomic divergence between paired primary and metastatic tumors.

Can metastatic-primary (M-P) genomic divergence measured from next generation sequencing reveal the natural history of metastatic dissemination? This remains an open question of utmost importance in facilitating a deeper understanding of metastatic progression, and thereby, improving its prevention. Here, we utilize mathematical and computational modeling to tackle this question as well as to provide a framework that illuminates the fundamental elements and evolutionary determinants of M-P divergence. Our framework facilitates the integration of sequencing detectability of somatic variants, and hence, paves the way towards bridging the measurable between-tumor heterogeneity with analytical modeling and interpretability. We show that the number of somatic variants of the metastatic seeding cell that are experimentally undetectable in the primary tumor, can be characterized as the path of the phylogenetic tree from the last appearing variant of the seeding cell back to the most recent detectable variant. We find that the expected length of this path is principally determined by the decay in detectability of the variants along the seeding cell's lineage; and thus, exhibits a significant dependence on the underlying tumor growth dynamics. A striking implication of this fact, is that dissemination from an advanced detectable subclone of the primary tumor can lead to an abrupt drop in the expected measurable M-P divergence, thereby breaking the previously assumed monotonic relation between seeding time and M-P divergence. This is emphatically verified by our single cell-based spatial tumor growth simulation, where we find that M-P divergence exhibits a non-monotonic relationship with seeding time when the primary tumor grows under branched and linear evolution. On the other hand, a monotonic relationship holds when we condition on the dynamics of progressive diversification, or by restricting the seeding cells to always originate from undetectable subclones. Our results highlight the fact that a precise understanding of tumor growth dynamics is the sine qua non for exploiting M-P divergence to reconstruct the chronology of metastatic dissemination. The quantitative models presented here enable further careful evaluation of M-P divergence in association with crucial evolutionary and sequencing parameters.

A population genetics perspective on the determinants of intra-tumor heterogeneity.

Cancer results from the acquisition of somatic alterations in a microevolutionary process that typically occurs over many years, much of which is occult. Understanding the evolutionary dynamics that are operative at different stages of progression in individual tumors might inform the earlier detection, diagnosis, and treatment of cancer. Although these processes cannot be directly observed, the resultant spatiotemporal patterns of genetic variation amongst tumor cells encode their evolutionary histories. Such intra-tumor heterogeneity is pervasive not only at the genomic level, but also at the transcriptomic, phenotypic, and cellular levels. Given the implications for precision medicine, the accurate quantification of heterogeneity within and between tumors has become a major focus of current research. In this review, we provide a population genetics perspective on the determinants of intra-tumor heterogeneity and approaches to quantify genetic diversity. We summarize evidence for different modes of evolution based on recent cancer genome sequencing studies and discuss emerging evolutionary strategies to therapeutically exploit tumor heterogeneity. This article is part of a Special Issue entitled: Evolutionary principles - heterogeneity in cancer?, edited by Dr. Robert A. Gatenby.

Centrosomal Protein 55 (CEP55) Drives Immune Exclusion and Resistance to Immune Checkpoint Inhibitors in Colorectal Cancer.

Colorectal cancer (CRC) currently ranks as the third most common cancer in the United States, and its incidence is on the rise, especially among younger individuals. Despite the remarkable success of immune checkpoint inhibitors (ICIs) in various cancers, most CRC patients fail to respond due to intrinsic resistance mechanisms. While microsatellite instability-high phenotypes serve as a reliable positive predictive biomarker for ICI treatment, the majority of CRC patients with microsatellite-stable (MSS) tumors remain ineligible for this therapeutic approach. In this study, we investigated the role of centrosomal protein 55 (CEP55) in shaping the tumor immune microenvironment in CRC. CEP55 is overexpressed in multiple cancer types and was shown to promote tumorigenesis by upregulating the PI3K/AKT pathway. Our data revealed that elevated CEP55 expression in CRC was associated with reduced T cell infiltration, contributing to immune exclusion. As CRC tumors progressed, CEP55 expression increased alongside sequential mutations in crucial driver genes (APC, KRAS, TP53, and SMAD4), indicating its involvement in tumor progression. CEP55 knockout significantly impaired tumor growth in vitro and in vivo, suggesting that CEP55 plays a crucial role in tumorigenesis. Furthermore, the CEP55 knockout increased CD8+ T cell infiltration and granzyme B production, indicating improved anti-tumor immunity. Additionally, we observed reduced regulatory T cell infiltration in CEP55 knockout tumors, suggesting diminished immune suppression. Most significantly, CEP55 knockout tumors demonstrated enhanced responsiveness to immune checkpoint inhibition in a clinically relevant orthotopic CRC model. Treatment with anti-PD1 significantly reduced tumor growth in CEP55 knockout tumors compared to control tumors, suggesting that inhibiting CEP55 could improve the efficacy of ICIs. Collectively, our study underscores the crucial role of CEP55 in driving immune exclusion and resistance to ICIs in CRC. Targeting CEP55 emerges as a promising therapeutic strategy to sensitize CRC to immune checkpoint inhibition, thereby improving survival outcomes for CRC patients.

Evolving copy number gains promote tumor expansion and bolster mutational diversification.

The timing and fitness effect of somatic copy number alterations (SCNA) in cancer evolution remains poorly understood. Here we present a framework to determine the timing of a clonal SCNA that encompasses multiple gains. This involves calculating the proportion of time from its last gain to the onset of population expansion (lead time) as well as the proportion of time prior to its first gain (initiation time). Our method capitalizes on the observation that a genomic segment, while in a specific copy number (CN) state, accumulates point mutations proportionally to its CN. Analyzing 184 whole genome sequenced samples from 75 patients across five tumor types, we commonly observe late gains following early initiating events, occurring just before the clonal expansion relevant to the sampling. These include gains acquired after genome doubling in more than 60% of cases. Notably, mathematical modeling suggests that late clonal gains may contain final-expansion drivers. Lastly, SCNAs bolster mutational diversification between subpopulations, exacerbating the circle of proliferation and increasing heterogeneity.

Breakpointer: using local mapping artifacts to support sequence breakpoint discovery from single-end reads.

SUMMARY: We developed Breakpointer, a fast algorithm to locate breakpoints of structural variants (SVs) from single-end reads produced by next-generation sequencing. By taking advantage of local non-uniform read distribution and misalignments created by SVs, Breakpointer scans the alignment of single-end reads to identify regions containing potential breakpoints. The detection of such breakpoints can indicate insertions longer than the read length and SVs located in repetitve regions which might be missd by other methods. Thus, Breakpointer complements existing methods to locate SVs from single-end reads. AVAILABILITY: https://github.com/ruping/Breakpointer CONTACT: ruping@molgen.mpg.de SUPPLEMENTARY INFORMATION: Supplementary material is available at Bioinformatics online.

Detecting genomic indel variants with exact breakpoints in single- and paired-end sequencing data using SplazerS.

MOTIVATION: The reliable detection of genomic variation in resequencing data is still a major challenge, especially for variants larger than a few base pairs. Sequencing reads crossing boundaries of structural variation carry the potential for their identification, but are difficult to map. RESULTS: Here we present a method for 'split' read mapping, where prefix and suffix match of a read may be interrupted by a longer gap in the read-to-reference alignment. We use this method to accurately detect medium-sized insertions and long deletions with precise breakpoints in genomic resequencing data. Compared with alternative split mapping methods, SplazerS significantly improves sensitivity for detecting large indel events, especially in variant-rich regions. Our method is robust in the presence of sequencing errors as well as alignment errors due to genomic mutations/divergence, and can be used on reads of variable lengths. Our analysis shows that SplazerS is a versatile tool applicable to unanchored or single-end as well as anchored paired-end reads. In addition, application of SplazerS to targeted resequencing data led to the interesting discovery of a complete, possibly functional gene retrocopy variant. AVAILABILITY: SplazerS is available from http://www.seqan.de/projects/ splazers. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Somatic variant detection from multi-sampled genomic sequencing data of tumor specimens using the ith.Variant pipeline.

A common technique for uncovering intra-tumor genomic heterogeneity (ITH) is variant detection. However, it can be challenging to reliably characterize ITH given uneven sample quality (e.g., depth of coverage, tumor purity, and subclonality). We describe a protocol for calling point mutations and copy number alterations using sequencing of multiple related clinical patient samples across diverse tissue, optimizing for sensitivity with specificity. The ith.Variant pipeline can be run on single- or multi-region whole-genome and whole-exome sequencing. For complete details on the use and execution of this protocol, please refer to Sun et al. (2017).1.

Hesperidin mitigates oxidative stress-induced ferroptosis in nucleus pulposus cells via Nrf2/NF-κB axis to protect intervertebral disc from degeneration.

Intervertebral disc degeneration (IVDD), a widely known contributor to low back pain (LBP), has been proved to be a global health challenging conundrum. Hesperidin (hesperetin-7-O-rutinoside, HRD) is a flavanone glycoside that belongs to the subgroup of citrus flavonoids with therapeutic effect on various diseases due to its anti-inflammatory, antioxidant properties. However, the effect of HRD on IVDD remains elusive. The human nucleus pulposus tissues were harvested for isolating human nucleus pulposus (HNP) cells to verify the expression of Nrf2. The biological effect of HRD on HNP cells were assessed in vitro, and the in vivo therapeutic effects of HRD were assessed in mice. Firstly, we found that the expression of Nrf2 was decreased with the progression of degeneration in degenerated human nucleus pulposus tissue. Subsequently, we confirmed that HRD could mitigate oxidative stress-induced ferroptosis in nucleus pulposus cells via enhancing the expression of Nrf2 axis and suppressing the NF-κB pathway to protect intervertebral disc from degeneration in vitro. Finally, the therapeutic effects of HRD were confirmed in vivo. The current study proved for the first time that HRD may protect HNP cells from degeneration by suppressing ferroptosis in an oxidative stress-dependent via enhancing the expression of Nrf2 and suppressing the NF-κB pathway. The evidence will provide a possible basis for future targeted treatment for IVDD.

The deubiquitinase USP11 ameliorates intervertebral disc degeneration by regulating oxidative stress-induced ferroptosis via deubiquitinating and stabilizing Sirt3.

Increasing studies have reported that intervertebral disc degeneration (IVDD) is the main contributor and independent risk factor for low back pain (LBP), it would be, therefore, enlightening that investigating the exact pathogenesis of IVDD and developing target-specific molecular drugs in the future. Ferroptosis is a new form of programmed cell death characterized by glutathione (GSH) depletion, and inactivation of the regulatory core of the antioxidant system (glutathione system) GPX4. The close relationship of oxidative stress and ferroptosis has been studied in various of diseases, but the crosstalk between of oxidative stress and ferroptosis has not been explored in IVDD. At the beginning of the current study, we proved that Sirt3 decreases and ferroptosis occurs after IVDD. Next, we found that knockout of Sirt3 (Sirt3-/-) promoted IVDD and poor pain-related behavioral scores via increasing oxidative stress-induced ferroptosis. The (immunoprecipitation coupled with mass spectrometry) IP/MS and co-IP demonstrated that USP11 was identified to stabilize Sirt3 via directly binding to Sirt3 and deubiquitinating Sirt3. Overexpression of USP11 significantly ameliorate oxidative stress-induced ferroptosis, thus relieving IVDD by increasing Sirt3. Moreover, knockout of USP11 in vivo (USP11-/-) resulted in exacerbated IVDD and poor pain-related behavioral scores, which could be reversed by overexpression of Sirt3 in intervertebral disc. In conclusion, the current study emphasized the importance of the interaction of USP11 and Sirt3 in the pathological process of IVDD via regulating oxidative stress-induced ferroptosis, and USP11-mediated oxidative stress-induced ferroptosis is identified as a promising target for treating IVDD.

Oncogene-like addiction to aneuploidy in human cancers.

Most cancers exhibit aneuploidy, but its functional significance in tumor development is controversial. Here, we describe ReDACT (Restoring Disomy in Aneuploid cells using CRISPR Targeting), a set of chromosome engineering tools that allow us to eliminate specific aneuploidies from cancer genomes. Using ReDACT, we created a panel of isogenic cells that have or lack common aneuploidies, and we demonstrate that trisomy of chromosome 1q is required for malignant growth in cancers harboring this alteration. Mechanistically, gaining chromosome 1q increases the expression of MDM4 and suppresses TP53 signaling, and we show that TP53 mutations are mutually-exclusive with 1q aneuploidy in human cancers. Thus, specific aneuploidies play essential roles in tumorigenesis, raising the possibility that targeting these "aneuploidy addictions" could represent a novel approach for cancer treatment.

Oncogene-like addiction to aneuploidy in human cancers.

Most cancers exhibit aneuploidy, but its functional significance in tumor development is controversial. Here, we describe ReDACT (Restoring Disomy in Aneuploid cells using CRISPR Targeting), a set of chromosome engineering tools that allow us to eliminate specific aneuploidies from cancer genomes. Using ReDACT, we created a panel of isogenic cells that have or lack common aneuploidies, and we demonstrate that trisomy of chromosome 1q is required for malignant growth in cancers harboring this alteration. Mechanistically, gaining chromosome 1q increases the expression of MDM4 and suppresses p53 signaling, and we show that TP53 mutations are mutually exclusive with 1q aneuploidy in human cancers. Thus, tumor cells can be dependent on specific aneuploidies, raising the possibility that these "aneuploidy addictions" could be targeted as a therapeutic strategy.

Modeling read counts for CNV detection in exome sequencing data.

Varying depth of high-throughput sequencing reads along a chromosome makes it possible to observe copy number variants (CNVs) in a sample relative to a reference. In exome and other targeted sequencing projects, technical factors increase variation in read depth while reducing the number of observed locations, adding difficulty to the problem of identifying CNVs. We present a hidden Markov model for detecting CNVs from raw read count data, using background read depth from a control set as well as other positional covariates such as GC-content. The model, exomeCopy, is applied to a large chromosome X exome sequencing project identifying a list of large unique CNVs. CNVs predicted by the model and experimentally validated are then recovered using a cross-platform control set from publicly available exome sequencing data. Simulations show high sensitivity for detecting heterozygous and homozygous CNVs, outperforming normalization and state-of-the-art segmentation methods.

Characterizing the ecological and evolutionary dynamics of cancer.

Tumor initiation and progression are somatic evolutionary processes driven by the accumulation of genetic alterations, some of which confer selective fitness advantages to the host cell. This gene-centric model has shaped the field of cancer biology and advanced understanding of cancer pathophysiology. Importantly, however, each genotype encodes diverse phenotypic traits that permit acclimation to varied microenvironmental conditions. Epigenetic and transcriptional changes also contribute to the heritable phenotypic variation required for evolution. Additionally, interactions between cancer cells and surrounding stromal and immune cells through autonomous and non-autonomous signaling can influence competition for survival. Therefore, a mechanistic understanding of tumor progression must account for evolutionary and ecological dynamics. In this Perspective, we outline technological advances and model systems to characterize tumor progression through space and time. We discuss the importance of unifying experimentation with computational modeling and opportunities to inform cancer control.

Global gene expression analysis reveals reduced abundance of putative microRNA targets in human prostate tumours.

BACKGROUND: Recently, microRNAs (miRNAs) have taken centre stage in the field of human molecular oncology. Several studies have shown that miRNA profiling analyses offer new possibilities in cancer classification, diagnosis and prognosis. However, the function of miRNAs that are dysregulated in tumours remains largely a mystery. Global analysis of miRNA-target gene expression has helped illuminate the role of miRNAs in developmental gene expression programs, but such an approach has not been reported in cancer transcriptomics. RESULTS: In this study, we globally analysed the expression patterns of miRNA target genes in prostate cancer by using several public microarray datasets. Intriguingly, we found that, in contrast to global mRNA transcript levels, putative miRNA targets showed a reduced abundance in prostate tumours relative to benign prostate tissue. Additionally, the down-regulation of these miRNA targets positively correlated with the number of types of miRNA target-sites in the 3' untranslated regions of these targets. Further investigation revealed that the globally low expression was mainly driven by the targets of 36 specific miRNAs that were reported to be up-regulated in prostate cancer by a miRNA expression profiling study. We also found that the transcript levels of miRNA targets were lower in androgen-independent prostate cancer than in androgen-dependent prostate cancer. Moreover, when the global analysis was extended to four other cancers, significant differences in transcript levels between miRNA targets and total mRNA backgrounds were found. CONCLUSION: Global gene expression analysis, along with further investigation, suggests that miRNA targets have a significantly reduced transcript abundance in prostate cancer, when compared with the combined pool of all mRNAs. The abnormal expression pattern of miRNA targets in human cancer could be a common feature of the human cancer transcriptome. Our study may help to shed new light on the functional roles of miRNAs in cancer transcriptomics.

Quantitative evidence for early metastatic seeding in colorectal cancer.

Both the timing and molecular determinants of metastasis are unknown, hindering treatment and prevention efforts. Here we characterize the evolutionary dynamics of this lethal process by analyzing exome-sequencing data from 118 biopsies from 23 patients with colorectal cancer with metastases to the liver or brain. The data show that the genomic divergence between the primary tumor and metastasis is low and that canonical driver genes were acquired early. Analysis within a spatial tumor growth model and statistical inference framework indicates that early disseminated cells commonly (81%, 17 out of 21 evaluable patients) seed metastases while the carcinoma is clinically undetectable (typically, less than 0.01 cm3). We validated the association between early drivers and metastasis in an independent cohort of 2,751 colorectal cancers, demonstrating their utility as biomarkers of metastasis. This conceptual and analytical framework provides quantitative in vivo evidence that systemic spread can occur early in colorectal cancer and illuminates strategies for patient stratification and therapeutic targeting of the canonical drivers of tumorigenesis.

Clonal replacement and heterogeneity in breast tumors treated with neoadjuvant HER2-targeted therapy.

Genomic changes observed across treatment may result from either clonal evolution or geographically disparate sampling of heterogeneous tumors. Here we use computational modeling based on analysis of fifteen primary breast tumors and find that apparent clonal change between two tumor samples can frequently be explained by pre-treatment heterogeneity, such that at least two regions are necessary to detect treatment-induced clonal shifts. To assess for clonal replacement, we devise a summary statistic based on whole-exome sequencing of a pre-treatment biopsy and multi-region sampling of the post-treatment surgical specimen and apply this measure to five breast tumors treated with neoadjuvant HER2-targeted therapy. Two tumors underwent clonal replacement with treatment, and mathematical modeling indicates these two tumors had resistant subclones prior to treatment and rates of resistance-related genomic changes that were substantially larger than previous estimates. Our results provide a needed framework to incorporate primary tumor heterogeneity in investigating the evolution of resistance.

Publisher Correction: Clonal replacement and heterogeneity in breast tumors treated with neoadjuvant HER2-targeted therapy.

The original version of this Article omitted from the Author Contributions statement that 'R.S. and J.G.R contributed equally to this work.' This has been corrected in both the PDF and HTML versions of the Article.

Simultaneously detection of genomic and expression alterations in prostate cancer using cDNA microarray.

BACKGROUND: Prostate cancer is a common disease among men but the knowledge of the prostate carcinogenesis is still limited. METHODS: cDNA microarray-based comparative genomic hybridization (CGH) and expression profiling were performed to screen the genomic and the expression changes in prostate cancer respectively. The two data were integrated to study the influence of genomic aberrations on gene expression and seek for the genes with their expression affected by the genomic aberrations. Real-time PCR was performed to evaluate the array data. RESULTS: Array-based CGH detected gains at 2q, 3p/q, 5q, 6q, 8q, 9p, 10p/q, 11q, 12p, 14q, and 19p/q and losses at 1p, 2p, 4q, 6p/q, 7p, 11p/q, 12q, 17p/q, 19p/q, and Xp/q in more than 20% prostate tumors and narrowed these aberrations. For example, the gain of 8q was mapped to five minimal regions. Novel aberrations were also identified, such as loss at Xq21.33-q22.2. Expression profiling discovered the significant biological processes involved in the prostate carcinogenesis, such as exogenous antigen presentation via MHC class II and protein ubiquitination. Integration analysis revealed a weak positive correlation between genomic copy number and gene expression level. Fifty-three genes showed their expression directly affected by the genomic aberrations possibly, including more than one member of Ras superfamily and major histocompatibility complex (MHC). These genes are involved in multiple biological processes. CONCLUSIONS: Integration of the CGH and expression data provided more information than separate analysis. Although the direct influence of genomic aberrations on gene expression seems weak, the influence can be extended by indirect regulation through a few directly affected genes. Because the influence can be persistent, the genes directly affected by the genomic aberrations may play key roles in the prostate carcinogenesis and are worth further analysis.