SEARCH · Search bioRxiv

Results for “Cancer Biology”

Search indexed bioRxiv preprints in genomics, neuroscience, cell biology and bioinformatics. Read source abstracts and check manuscript versions; preprints are not peer reviewed.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 1,225 records · Page 68Linked to original sources

bioRxiv2017

Bcl-xL as a poor prognostic biomarker and predictor of response to adjuvant chemotherapy specifically in BRAF-mutant stage II and III colon cancer

BackgroundBRAF mutation occurs in 8-15% of colon cancers (CC), and is associated with poor prognosis in metastatic disease. Compared to wild-type BRAF (BRAFWT) disease, stage II/III CC patients with BRAF mutant (BRAFMT) tumors have shorter overall survival after relapse; however, time-to-relapse is not significantly different. The aim of this investigation was to identify, and validate, novel predictors of relapse of stage II/III BRAFMT CC.\n\nPatients and methodsWe used gene expression data from a cohort of 460 patients (GSE39582) to perform a supervised classification analysis based on risk-of-relapse within BRAFMT stage II/III CC, to identify transcriptomic biomarkers associated with prognosis within this genotype. These findings were validated using immunohistochemistry in an independent population-based cohort of Stage II/III CC (n=691), applying Cox proportional hazards analysis to determine associations with survival.\n\nResultsHigh gene expression levels of Bcl-xL, a key regulator of apoptosis, were associated with increased risk of relapse, specifically in BRAFMT tumors (HR=8.3, 95% CI 1.7-41.7), but not KRASMT/BRAFWT or KRASWT/BRAFWT tumors. High Bcl-xL protein expression in BRAFMT, untreated, stage II/III CC was confirmed to be associated with an increased risk of death in an independent cohort (HR=12.13, 95% CI 2.49-59.13). Additionally, BRAFMT tumors with high levels of Bcl-xL protein expression appeared to benefit from adjuvant chemotherapy (P for interaction =0.006), indicating the potential predictive value of Bcl-xL expression in this setting.\n\nConclusionsThese findings provide evidence that Bcl-xL gene and/or protein expression identifies a poor prognostic subgroup of BRAFMT stage II/III CC patients, who may benefit from adjuvant chemotherapy.\n\nKey MessageO_LIUsing a combination of computational biology discovery and immunohistochemistry validation in independent patient cohorts, we show that high expression of the apoptosis regulator Bcl-xL is associated with disease relapse specifically within BRAF mutant stage II/III colon cancer.\nC_LIO_LIThis data could enable tailored disease management to reduce relapse rates in the most aggressive subtype.\nC_LI

cancer biology↗

bioRxiv2016

Exploiting expression patterns across multiple gene isoforms to identify radiation response biomarkers in early-stage breast cancer patients.

In an effort to understand the underlying biology of radiation response along with whole transcriptome effects of preoperative radiotherapy in early-stage breast tumors, we propose two efficient score-based statistical methods that exploit gene expression patterns across all available gene transcript isoforms and identify potential biomarkers in the form of differentially expressed genes and differentially enriched gene-sets. We demonstrate the effectiveness of these two methods using extensive simulation studies that show that both of our methods give improved performance, in terms of statistical power, over the most commonly used methods. By exploiting radiation-induced changes in all available gene transcript isoforms, we identified several statistically significant differentially expressed genes related to PI3K-AKT and JAK-STAT signaling pathways along with radiation-induced oncogenic signaling pathways and tumor microenvironment gene signatures that could be potential targets to improve response to radiotherapy in breast tumors.

bioinformatics↗

bioRxiv2017

Analysis of RAS as a tumor suppressor

The RAS GTPases are among the best-understood oncogenes that promote human cancer. Many have argued that non-mutated, wild-type, RAS also functions as a tumor suppressor. The arguments for RAS tumor suppressor activity often involve data that are claimed to be inconsistent with known principles of RAS biology. RAS tumor suppressor activity is invoked to explain these observations. Here, we consider an alternative hypothesis: these data are actually consistent with RAS biology. We investigate by using our previously developed mathematical model of RAS regulation. We find that three of five arguments for RAS having tumor suppressor activity are based upon data that the model demonstrates are actually consistent with known RAS biology. We also find that the other two types of data interpreted to indicate a tumor suppressor effect can be explained by our model with the additional assumption that RAS protein expression does not vary proportionally with gene dosage. Measurements of RAS protein expression as a function of gene dosage could help resolve whether or not RAS has tumor suppressor activity. Overall, we conclude that the evidence for RAS having tumor suppressor activity is much less strong that it has appeared.

cancer biology↗

bioRxiv2017

RNA-mediated Genomic Arrangements in Mammalian Cells

One of the hallmarks of cancer is the formation of oncogenic fusion genes as a result of chromosomal translocations. Fusion genes are presumed to occur prior to fusion RNA expression. However, studies have reported the presence of fusion RNAs in individuals who were negative for chromosomal translocations. These observations give rise to \"the cart before the horse\" hypothesis, in which fusion RNA precedes the fusion gene and guides the genomic rearrangements that ultimately result in gene fusions. Yet RNA-mediated genomic rearrangement in mammalian cells has never been demonstrated. Here we provide evidence that expression of a chimeric RNA drives formation of a specified gene fusion via genomic rearrangement in mammalian cells. The process is (1) specified by the sequence of chimeric RNA involved, (2) facilitated by physiological hormone levels, (3) permissible regardless of intra-chromosomal (TMPRSS2-ERG) or inter-chromosomal (TMPRSS2-ETV1) fusion, and (4) can occur in normal cells prior to malignant transformation. We demonstrate that, contrary to \"the cart before the horse\" model, it is the antisense rather than sense chimeric RNAs that effectively drive gene fusion, and that this disparity can be explained by transcriptional conflict. Furthermore, we identified an endogenous RNA AZI1 that acts as the initiator RNA to induce TMPRSS2-ERG fusion. RNA-driven gene fusion demonstrated in this report provides important insight in early disease mechanism, and could have fundamental implications in the biology of mammalian genome stability, as well as gene editing technology via mechanisms native to mammalian cells.

cancer biology↗

bioRxiv2017

The role of telomere shortening in carcinogenesis: A hybrid stochastic-deterministic approach

Genome instability is a characteristic of most cancers, contributing to the acquisition of genetic alterations that drive tumor progression. One important source of genome instability is linked to telomere dysfunction in cells with critically short telomeres that lack p53-mediated surveillance of genomic integrity. Here we research the probability that cancer emerges through an evolutionary pathway that includes a telomere-induced phase of genome instability. To implement our models we use a hybrid stochastic-deterministic approach, which allows us to perform large numbers of simulations using biologically realistic population sizes and mutation rates, circumventing the traditional limitations of fully stochastic algorithms. The hybrid methodology should be easily adaptable to a wide range of evolutionary problems. In particular, we model telomere shortening and the acquisition of two mutations: Telomerase activation and p53 inactivation. We find that the death rate of unstable cells, and the number of cell divisions that p53 mutants can sustain beyond the normal senescence setpoint determine the likelihood that the first double mutant originates in a cell with telomere-induced instability. The model has applications to an influential telomerase-null mouse model and p16 silenced human cells. We end by discussing algorithmic performance and a measure for the accuracy of the hybrid approximation.

cancer biology↗

bioRxiv2018

Pathway and network analysis of more than 2,500 whole cancer genomes

The catalog of cancer driver mutations in protein-coding genes has greatly expanded in the past decade. However, non-coding cancer driver mutations are less well-characterized and only a handful of recurrent non-coding mutations, most notably TERT promoter mutations, have been reported. Motivated by the success of pathway and network analyses in prioritizing rare mutations in protein-coding genes, we performed multi-faceted pathway and network analyses of non-coding mutations across 2,583 whole cancer genomes from 27 tumor types compiled by the ICGC/TCGA PCAWG project. While few non-coding genomic elements were recurrently mutated in this cohort, we identified 93 genes harboring non-coding mutations that cluster into several modules of interacting proteins. Among these are promoter mutations associated with reduced mRNA expression in TP53, TLE4, and TCF4. We found that biological processes had variable proportions of coding and non-coding mutations, with chromatin remodeling and proliferation pathways altered primarily by coding mutations, while developmental pathways, including Wnt and Notch, altered by both coding and non-coding mutations. RNA splicing was primarily targeted by non-coding mutations in this cohort, with samples containing non-coding mutations exhibiting similar gene expression signatures as coding mutations in well-known RNA splicing factors. These analyses contribute a new repertoire of possible cancer genes and mechanisms that are altered by non-coding mutations and offer insights into additional cancer vulnerabilities that can be investigated for potential therapeutic treatments.

cancer biology↗

bioRxiv2026

Single-cell informed metabolic modeling reveals organ-specific metabolic adaptations in breast cancer organotropism

Breast cancer organotropism is driven by interactions between tumor cells and organ-specific microenvironments that support metastatic growth. To better understand the metabolic basis of organ-specific metastasis, we integrated single-cell transcriptomics with constraint-based systems biology to generate context-specific metabolic models of breast cancer metastasis to the liver, bone, and brain. Our analysis identified both common and organ-specific metabolic changes, suggesting that metastatic cells share a core metabolic program while also adapting to the metabolic environment of each target organ. Primary tumors with metastatic potential showed early alterations in nucleotide metabolism, transport reactions, and energy-related pathways, indicating metabolic changes before metastatic spread. Metabolic transformation analysis identified key metabolic regulators involved in the tricarboxylic acid (TCA) cycle, oxidative phosphorylation, redox balance, and metabolite transport. Integration with CRISPR gene essentiality data further highlighted metabolically important genes as potential therapeutic targets. In addition, analysis of organ-specific secreted metabolites revealed distinct metabolic signatures associated with metastatic colonization of the liver, bone, and brain. Overall, our single-cell-informed metabolic modeling approach shows that breast cancer organotropism is associated with both shared and organ-specific metabolic adaptations. The study provides a framework for identifying potential metabolic vulnerabilities that could be targeted to treat metastatic breast cancer.

systems biology↗

bioRxiv2017

Somatic inactivating PTPRJ mutations and dysregulated pathways identified in canine melanoma by integrated comparative genomic analysis

Canine malignant melanoma, a significant cause of mortality in domestic dogs, is a powerful comparative model for human melanoma, but little is known about its genetic etiology. We mapped the genomic landscape of canine melanoma through multi-platform analysis of 37 tumors (31 mucosal, 3 acral, 2 cutaneous, and 1 uveal) and 17 matching constitutional samples including long- and short-insert whole genome sequencing, RNA sequencing, array comparative genomic hybridization, single nucleotide polymorphism array, and targeted Sanger sequencing analyses. We identified novel predominantly truncating mutations in the putative tumor suppressor gene PTPRJ in 19% of cases. No BRAF mutations were detected, but activating RAS mutations (24% of cases) occurred in conserved hotspots in all cutaneous and acral and 13% of mucosal subtypes. MDM2 amplifications (24%) and TP53 mutations (19%) were mutually exclusive. Additional low-frequency recurrent alterations were observed amidst low point mutation rates, an absence of ultraviolet light mutational signatures, and an abundance of copy number and structural alterations. Mutations that modulate cell proliferation and cell cycle control were common and highlight therapeutic axes such as MEK and MDM2 inhibition. This mutational landscape resembles that seen in BRAF wild-type and sun-shielded human melanoma subtypes. Overall, these data inform biological comparisons between canine and human melanoma while suggesting actionable targets in both species.\n\nAUTHOR SUMMARYMelanoma, an aggressive cancer arising from transformed melanocytes, commonly occurs in pet dogs. Unlike human melanoma, which most often occurs in sun-exposed cutaneous skin, canine melanoma typically arises in sun-shielded oral mucosa. Clinical features of canine melanoma resemble those of human melanoma, particularly the less common sun-shielded human subtypes. However, whereas the genomic basis of diverse human melanoma subtypes is well understood, canine melanoma genomics remain poorly defined. Similarly, although diverse new treatments for human melanoma based on a biologic disease understanding have recently shown dramatic improvements in outcomes for these patients, treatments for canine melanoma are limited and outcomes remain universally poor. Detailing the genomic basis of canine melanoma thus provides untapped potential for improving the lives of pet dogs while also helping to establish canine melanoma as a comparative model system for informing human melanoma biology and treatment. In order to better define the genomic landscape of canine melanoma, we performed multi-platform characterization of 37 tumors. Our integrated analysis confirms that these tumors commonly contain mutations in canine orthologs of human cancer genes such as RAS, MDM2, and TP53 as well mutational patterns that share important similarities with human melanoma subtypes. We have also found a new putative cancer gene, PTPRJ, frequently mutated in canine melanoma. These data will guide additional biologic and therapeutic studies in canine melanoma while framing the utility of comparative studies of canine and human cancers more broadly.

cancer biology↗

bioRxiv2017

Population-level distribution and putative immunogenicity of cancer neoepitopes

BackgroundTumor neoantigens are a driver of cancer immunotherapy response; however, current neoantigen prediction tools produce many candidates that require further prioritization for research/clinical applications. Additional filtration criteria and population-level understanding may help to produce refined lists of putative neoantigens. Herein, we show neoepitope immunogenicity is likely related to measures of peptide novelty and report population-level behavior of these and other metrics.\n\nMethodsWe propose four peptide novelty metrics to refine predicted neoantigenicity: tumor vs. paired normal peptide binding affinity difference, tumor vs. paired normal peptide sequence similarity, tumor vs. closest human peptide sequence similarity, and tumor vs. closest microbial peptide sequence similarity. We apply these metrics to tumor neoepitopes predicted from somatic missense mutations in The Cancer Genome Atlas (TCGA) and a cohort of melanoma patients, as well as to a group of peptides with neoepitope-specific immune response data using an extension of pVAC-Seq [1].\n\nResultsWe show neoepitope burden varies across TCGA disease sites and HLA alleles, with surprisingly low repetition of neoepitope sequences across patients or neoepitope preferences among sets of HLA alleles. Only 20.3% of predicted neoepitopes across TCGA patients displayed novel binding change based on our binding affinity difference criteria. Similarity of amino acid sequence was typically high between paired tumor-normal epitopes, but in 24.6% of cases, neoepitopes were more similar to other human peptides, or even to bacterial (56.8% of cases) or viral peptides (15.5% of cases), than their paired normal counterparts. Applied to peptides with neoepitope-specific immune response, a linear model incorporating neoepitope binding affinity, protein sequence similarity between neoepitopes and their closest viral peptides, and paired binding affinity difference was able to predict immunogenicity with an AUROC of 0.66.\n\nConclusionsOur proposed neoepitope prioritization criteria emphasize neoepitope novelty and refine patient neoepitope predictions for focus on biologically meaningful candidate neoantigens. We have demonstrated that neoepitopes should be considered not only with respect to their paired normal epitope, but with respect to the entire human proteome, as well as bacterial and viral peptides, with potential implications for neoepitope immunogenicity and personalized vaccines for cancer treatment. We conclude that putative neoantigens are highly variable across individuals as a function of both cancer genetics and personalized HLA repertoire, while the overall behavior of filtration criteria reflects predictable patterns.

cancer biology↗

bioRxiv2016

Consensus Gene Expression Subtypes Of Epithelial Tumors

While the heterogeneity of cancer is increasingly appreciated, it is also clear that recurrently deregulated pathways are shared between tumors across tissue types. To identify similarities in subsets of tumors from multiple epithelial organs, we performed transcriptome profile analysis of different epithelial tumors and cell lines (n=2928) from 17 different organs. We identified three to seven consensus gene expression subtypes in epithelial tumors and cell lines, irrespective of the organ-specific origin. These consensus subtypes showed biological significance. Moreover, we identified specific gene signatures that could be used to develop clinical assays for future application of this classification system. Overall, our study identifies consensus transcriptome subtypes across organ-specific tumors and highlights new avenues for precision therapy irrespective of the organ of origin.

Cancer Biology↗

bioRxiv2017

Whole-exome sequencing of plasma cell-free DNA portrays the somatic mutation landscape of refractory metastatic colorectal cancer and enables the discovery of mutated KDR/VEGFR2 receptors as modulators of anti-angiogenic therapies.

The non-invasive detection of cancer mutations is a breakthrough in oncology. Here, we applied whole-exome sequencing of matched germline and basal plasma cell-free DNA samples (WES-cfDNA) on a RAS/BRAF/PIK3CA wild-type metastatic colorectal cancer patient with primary resistance to standard treatment regimens including VEGFR inhibitors. Using WES-cfDNA, we could detect 73% (54/74) of the somatic mutations uncovered by WES-tumor including a variety of mutation types: frameshift (indels), missense, noncoding (splicing), and nonsense mutations. Additionally, WES-cfDNA discovered 14 high-confidence somatic mutations not identified by WES-tumor. Importantly, in the absence of the tumor specimen, WES-cfDNA could identify 68 of the 88 (77.3%) total mutations that could be identified by both techniques. Of tumor biology relevance, we identified the novel KDR/VEGFR2 L840F somatic mutation, which we showed was a clonal mutation event in this tumor. Comprehensive in vitro and in vivo functional assays confirmed that L840F causes strong resistance to anti-angiogenic drugs, whereas the KDR/VEGFR2 hot-spot mutant R1032Q confers sensitivity to cabozantinib. Moreover, we found a 1-3% of recurrent KDR somatic mutations across large and non-overlapping cancer sequencing projects, and the majority of these mutations were located in protein residues frequently mutated in other cancer-relevant kinases, such as EGFR, ABL1, and ALK, suggesting a functional role.\n\nIn summary, the current study highlights the capability of exomic sequencing of cfDNA from plasma of cancer patients as a powerful platform for somatic landscape analysis and discovery of resistance-associated cancer mutations. Because of its advantage to generate results highly concordant to those of tumor sequencing without the hurdle of conventional tumor biopsies, we anticipate that WES-cfDNA will become frequently used in oncology. Moreover, our study identified for the first-time KDR/VEGFR2 somatic mutations as potential genetic biomarkers of response to anti-angiogenic cancer therapies and will serve as reference for further studies on the topic.

cancer biology↗

bioRxiv2017

Imaging specific cellular glycan structures using glycosyltransferases via click chemistry

Heparan sulfate (HS) is a polysaccharide fundamentally important for biologically activities. T/Tn antigens are universal carbohydrate cancer markers. Here, we report the specific imaging of these carbohydrates using a mesenchymal stem cell line and human umbilical vein endothelial cells (HUVEC). The staining specificities were demonstrated by comparing imaging of different glycans and validated by either removal of target glycans, which results in loss of signal, or installation of target glycans, which results in gain of signal. As controls, representative key glycans including O-GlcNAc, lactosaminyl glycans and hyaluronan were also imaged. HS staining revealed novel architectural features of the extracellular matrix (ECM) of HUVEC cells. Results from T/Tn antigen staining suggest that O-GalNAcylation is a rate-limiting step for O-glycan synthesis. Overall, these highly specific approaches for HS and T/Tn antigen imaging should greatly facilitate the detection and functional characterization of these biologically important glycans.

molecular biology↗

bioRxiv2018

Comprehensive 2D and 3D phenotypic characterization of human invasive lobular carcinoma cell lines

Invasive lobular carcinoma (ILC) is the second most common subtype of breast cancer following invasive ductal carcinoma (IDC) and characterized by the loss of E-cadherin-mediated adherens junctions. Despite displaying unique histological and clinical features, ILC still remains a chronically understudied disease with limited knowledge on the available laboratory research models. To this end, herein we report a comprehensive 2D and 3D phenotypic characterization of four Estrogen Receptor-positive human ILC cell lines - MDA-MB-134, SUM44, MDA-MB-330 and BCK4. Compared to the IDC cell lines MCF7, T47D and MDA-MB-231, ultra-low attachment culture conditions revealed a remarkable anchorage-independence ability that was unique to the ILC cells, a feature not evident in soft agar gels. 3D Collagen I and Matrigel culture indicated a generally loose morphology for the ILC cell lines, which exhibited differing preferences for adhesion to ECM proteins in 2D. Furthermore, ILC cells had limited migration and invasion ability in wound-scratch and transwell assays with the exception of haptotaxis to Collagen I. Transcriptional comparison of the cell lines confirmed the decreased cell proliferation and E-cadherin-mediated intercellular junctions in ILC, while uncovering the induction of novel pathways related to cyclic nucleotide phosphodiesterase activity, ion channels, drug metabolism and alternative cell adhesion molecules such as N-cadherin, some of which were also differentially regulated in ILC versus IDC tumors. Altogether, these studies will serve as an invaluable resource for the breast cancer research community and facilitate further functional discoveries towards understanding ILC, identifying novel drug targets and ultimately improving the outcome of patients with ILC.\n\nAuthors ContributionsConception and design: N. Tasdemir, NE. Davidson, S. Oesterreich\n\nDevelopment of methodology: N. Tasdemir, L. Zhu, GC. Tseng, S. Oesterreich\n\nAcquisition of data (performed experiments, processed data, etc.): N. Tasdemir, E. Bossart, Z. Li, Z. Li\n\nAnalysis and interpretation of data (e.g. biological interpretation, statistical analysis, computational analysis): N. Tasdemir, Z. Li, KM. Levine, NE. Davidson, S. Oesterreich\n\nWriting, review and/or revision of the manuscript: N. Tasdemir, Z. Li, KM. Levine, BM. Jacobson, GC. Tseng, NE. Davidson, S. Oesterreich\n\nStudy supervision: NE. Davidson and S. Oesterreich

cancer biology↗

bioRxiv2017

A simple rule for the evolution of fast dispersal at the edge of expanding populations

Predicting evolution of expanding populations is critical to control biological threats such as invasive species and cancer metastasis. Expansion is primarily driven by reproduction and dispersal, but nature abounds with examples of evolution where organisms pay a reproductive cost to disperse faster. When does selection favor this survival of the fastest? We searched for a simple rule, motivated by evolution experiments where swarming bacteria evolved into an hy-perswarmer mutant which disperses[~] 100% faster but pays a growth cost of [~] 10% to make many copies of its flagellum. We analyzed a two-species model based on the Fisher equation to explain this observation: the population expansion rate (v) results from an interplay of growth (r) and dispersal (D) and is independent of the carrying capacity: [Formula]. A mutant can take over the edge only if its expansion rate (v2) exceeds the expansion rate of the established species (v1); this simple condition (v2 > v1) determines the maximum cost in slower growth that a faster mutant can pay and still be able to take over. Numerical simulations and time-course experiments where we tracked evolution by imaging bacteria suggest that our findings are general: less favorable conditions delay but do not entirely prevent the success of the fastest. Thus, the expansion rate defines a traveling wave fitness, which could be combined with trade-offs to predict evolution of expanding populations.

evolutionary biology↗

bioRxiv2017

DNAJB1-PRKACA fusion kinase drives tumorigenesis and interacts with β-catenin and the liver regenerative response.

A segmental deletion resulting in DNAJB1-PRKACA gene fusion is now recognized as the signature genetic event of fibrolamellar hepatocellular carcinoma (FL-HCC), a rare but lethal liver cancer that primarily affects adolescents and young adults. Here, we implement CRISPR/Cas9 genome editing and transposon-mediated somatic gene transfer to demonstrate that expression of both the endogenous fusion protein or a chimeric cDNA leads to the formation of indolent liver tumors in mice that closely resemble human FL-HCC. Notably, overexpression of the wild type PRKACA was unable to fully recapitulate the oncogenic activity of DNAJB1-PRKACA, implying that FL-HCC does not simply result from enhanced PRKACA expression. Tumorigenesis was significantly enhanced by genetic activation of {beta}-catenin, an observation supported by evidence of recurrent Wnt pathway mutations in human FL-HCC, as well as treatment with hepatotoxin 3,5-diethoxycarbonyl-1,4-dihydrocollidine (DDC), which causes tissue injury, inflammation and fibrosis. Our study validates the DNAJB1-PRKACA fusion kinase as an oncogenic driver and candidate drug target for FL-HCC and establishes a practical model for preclinical studies to identify strategies to treat this disease.\n\nSignificanceEfforts to understand and treat FL-HCC have been confounded by a lack of models that accurately reflect the genetics and biology of the disease. Here, we demonstrate that the Dnajb1-Prkaca gene fusion drives tumorigenesis in mice, and that fusion to DNAJB1 drives FL-HCC initiation more effectively than wild type PRKACA overexpression. The requirement of the PRKACA kinase domain in tumor initiation establishes the potential utility of kinase inhibitors targeting the fusion. By identifying genetic and environmental factors that can enhance the consistency and aggressiveness of disease progression, we reveal biological characteristics of the disease and advance a robust platform for future pre-clinical studies.

cancer biology↗

bioRxiv2018

Leveraging single cell RNA sequencing experiments to model intra-tumor heterogeneity

PURPOSEMany cancers can be treated with targeted therapy. Almost inevitably, tumors develop resistance to targeted therapy, either from preexistence or by evolving new genotypes and traits. Intra-tumor heterogeneity serves as a reservoir for resistance, which often occurs due to selection of minor cellular sub-clones. On the level of gene expression, the clonal heterogeneity can only be revealed by high-dimensional single cell methods. We propose to use a general diversity index (GDI) to quantify heterogeneity on multiple scales and relate it to disease evolution.\n\nMETHODSWe focused on individual patient samples probed with single cell RNA sequencing to describe heterogeneity. We developed a pipeline to analyze single cell data, via sample normalization, clustering and mathematical interpretation using a generalized diversity measure, and exemplify the utility of this platform using single cell data.\n\nRESULTSWe focused on three sources of RNA sequencing data: two healthy bone marrow (BM) samples, two acute myeloid leukemia (AML) patients, each sampled before and after BM transplant (BMT), four samples of pre-sorted lineages, and six lung carcinoma patients with multi-region sampling. While healthy/normal samples scored low in diversity overall, GDI further quantified in which respect these samples differed. While a widely used Shannon diversity index sometimes reveals less differences, GDI exhibits differences in the number of potential key drivers or clonal richness. Comparing pre and post BMT AML samples did not reveal differences in heterogeneity, although they can be very different biologically.\n\nCONCLUSIONGDI can quantify cellular heterogeneity changes across a wide spectrum, even when standard measures, such as the Shannon index, do not. Our approach offers wide applications to quantify heterogeneity across samples and conditions.

cancer biology↗

bioRxiv2017

Sensitivity analysis based ranking reveals unknown biological hypotheses for down regulated genes in time buffer during administration of PORCN-WNT inhibitor ETC-1922159 in CRC

In a recent development of the PORCN-WNT inhibitor ETC-1922159 for colorectal cancer, a list of down-regulated genes were recorded in a time buffer after the administration of the drug. The regulation of the genes were recorded individually but it is still not known which higher ([≥] 2) order interactions might be playing a greater role after the administration of the drug. In order to reveal the priority of these higher order interactions among the down-regulated genes or the likely unknown biological hypotheses, a search engine was developed based on the sensitivity indices of the higher order interactions that were ranked using a support vector ranking algorithm and sorted. For example, LGR family (Wnt signal enhancer) is known to neutralize RNF43 (Wnt inhibitor). After the administration of ETC-1922159 it was found that using HSIC (and rbf, linear and laplace variants of kernel) the rankings of the interaction between LGR5-RNF43 were 61, 114 and 85 respectively. Rankings for LGR6-RNF43 were 1652, 939 and 805 respectively. The down-regulation of LGR family after the drug treatment is evident in these rankings as it takes bottom priorities for LGR5-RNF43 interaction. The LGR6-RNF43 takes higher ranking than LGR5-RNF43, indicating that it might not be playing a greater role as LGR5 during the Wnt enhancing signals. These rankings confirm the efficacy of the proposed search engine design. Conclusion: Prioritized unknown biological hypothesis form the basis of further wet lab tests with the aim to reduce the cost of (1) wet lab experiments (2) combinatorial search and (3) lower the testing time for biologist who search for influential interactions in a vast combinatorial search forest. From in silico perspective, a framework for a search engine now exists which can generate rankings for nth order interactions in Wnt signaling pathway, thus revealing unknown/untested/unexplored biological hypotheses and aiding in understanding the mechanism of the pathway. The generic nature of the design can be applied to any signaling pathway or phenomena under investigation where a prioritized order of interactions among the involved factors need to be investigated for deeper understanding. Future improvements of the design are bound to facilitate medical specialists/oncologists in their respective investigations.\n\nSignificanceRecent development of PORCN-WNT inhibitor enantiomer ETC-1922159 cancer drug show promise in suppressing some types of colorectal cancer. However, the search and wet lab testing of unknown/unexplored/untested biological hypotheses in the form of combinations of various intra/ extracellular factors/genes/proteins affected by ETC-1922159 is not known. Currently, a major problem in biology is to cherry pick the combinations based on expert advice, literature survey or guesses to investigate a particular combinatorial hypothesis. A search engine has be developed to reveal and prioritise these unknown/untested/unexplored combinations affected by the inhibitor. These ranked unknown biological hypotheses facilitate in narrowing down the investigation in a vast combinatorial search forest of ETC-1922159 affected synergistic-factors.

cancer biology↗

bioRxiv2014

Chromothripsis-like patterns are recurring but heterogeneously distributed features in a survey of 22,347 cancer genome screens

BackgroundChromothripsis is a recently discovered phenomenon of genomic rearrangement, possibly arising during a single genome-shattering event. This could provide an alternative paradigm in cancer development, replacing the gradual accumulation of genomic changes with a \"one-off\" catastrophic event. However, the term has been used with varying operational definitions, with the minimal consensus being a large number of locally clustered copy number aberrations. The mechanisms underlying these chromothripsis-like patterns (CTLP) and their specific impact on tumorigenesis are still poorly understood.\n\nResultsHere, we identified CTLP in 918 cancer samples, from a dataset of more than 22,000 oncogenomic arrays covering 132 cancer types. Fragmentation hotspots were found to be located on chromosome 8, 11, 12 and 17. Among the various cancer types, soft-tissue tumors exhibited particularly high CTLP frequencies. Genomic context analysis revealed that CTLP rearrangements frequently occurred in genomes that additionally harbored multiple copy number aberrations (CNAs). An investigation into the affected chromosomal regions showed a large proportion of arm-level pulverization and telomere related events, which would be compatible to a number of underlying mechanisms. We also report evidence that these genomic events may be correlated with patient age, stage and survival rate.\n\nConclusionsThrough a large-scale analysis of oncogenomic array data sets, this study characterized features associated with genomic aberrations patterns, compatible to the spectrum of \"chromothripsis\"-definitions as previously used. While quantifying clustered genomic copy number aberrations in cancer samples, our data indicates an underlying biological heterogeneity behind these chromothripsis-like patterns, beyond a well defined \"chromthripsis\" phenomenon.

Genomics↗