SEARCH · bioRxiv Science

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 Read source abstracts and check manuscript versions; preprints are not peer reviewed.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 73 records · Page 4Linked to original sources

bioRxiv2016

Mutation signatures reveal biological processes in human cancer

Replication errors in the genome accumulate from a variety of mutational processes, which leave a history of mutations on the affected genome. The relative contribution of each mutational process has been characterized by non-negative matrix factorization and has lead to deeper insight into both mutational and repair processes contributing to cancer. However current implementations of NMF have left unresolved some specific patterns that should be present in the mutation data and have not generated signatures designed for classification. Here, we use a variant of NMF, termed non-smooth NMF, to generate sparse matrix factorizations of somatic mutation profiles present in 7129 tumors. nsNMF factorization revealed 21 mutational signatures. We found three APOBEC mutational processes clearly segregating with the published APOBEC enzymology and trans-lesion repair processes. We discovered several signatures differed between geographic locations even between closely related tissues.

Genomics↗

bioRxiv2017

Extracting a Biologically Relevant Latent Space from Cancer Transcriptomes with Variational Autoencoders

The Cancer Genome Atlas (TCGA) has profiled over 10,000 tumors across 33 different cancer-types for many genomic features, including gene expression levels. Gene expression measurements capture substantial information about the state of each tumor. Certain classes of deep neural network models are capable of learning a meaningful latent space. Such a latent space could be used to explore and generate hypothetical gene expression profiles under various types of molecular and genetic perturbation. For example, one might wish to use such a model to predict a tumors response to specific therapies or to characterize complex gene expression activations existing in differential proportions in different tumors. Variational autoencoders (VAEs) are a deep neural network approach capable of generating meaningful latent spaces for image and text data. In this work, we sought to determine the extent to which a VAE can be trained to model cancer gene expression, and whether or not such a VAE would capture biologically-relevant features. In the following report, we introduce a VAE trained on TCGA pan-cancer RNA-seq data, identify specific patterns in the VAE encoded features, and discuss potential merits of the approach. We name our method \"Tybalt\" after an instigative, cat-like character who sets a cascading chain of events in motion in Shakespeares \"Romeo and Juliet\". From a systems biology perspective, Tybalt could one day aid in cancer stratification or predict specific activated expression patterns that would result from genetic changes or treatment effects.

bioinformatics↗

bioRxiv2017

Hyperactivation of extracellular signal-regulated kinase (ERK) by RAS-mediated signaling or inhibition of dual specificity phosphatase 6 (DUSP6) is associated with toxicity in lung adenocarcinoma cells with mutations in KRAS or EGFR

We recently described the synthetic lethality that results when mutant KRAS and mutant EGFR are coexpressed in human lung adenocarcinoma (LUAD) cells, revealing the biological basis for the mutual exclusivity of KRAS and EGFR mutations in lung cancers. We have now further defined the biochemical events responsible for the toxic effects of signaling through the RAS pathway. By combining pharmacological and genetic approaches, we have developed multiple lines of evidence that signaling through extracellular signal-regulated kinases (ERK1/2) mediates the toxicity. These findings imply that tumors with mutant oncogenes that drive signaling through the RAS pathway must restrain the activity of ERK1/2 to avoid cell toxicities and enable tumor growth. In particular, a dual specificity phosphatase, DUSP6, regulates phosphorylated (P)-ERK levels in lung adenocarcinoma cells, providing negative feedback to the RAS signaling pathway. Accordingly, inhibition of DUSP6 is cytotoxic in LUAD cells driven by either mutant KRAS or mutant EGFR, phenocopying the effects of co-expression of mutant KRAS and EGFR. Together, these data suggest that targeting DUSP6 or other feedback regulators of the EGFR-KRAS-ERK pathway may offer a strategy for treating certain cancers by exceeding an upper threshold of RAS-mediated signaling.

cancer biology↗

bioRxiv2018

Classification of breast tumours into molecular apocrine, luminal and basal groups based on an explicit biological model

The gene expression profiles of human breast tumours fall into three main groups that have been called luminal, basal and either HER2-enriched or molecular apocrine. To escape from the circularity of descriptive classifications based purely on gene signatures I describe a biological classification based on a model of the mammary lineage. In this model I propose that the third group is a tumour derived from a mammary hormone-sensing cell that has undergone apocrine metaplasia. I first split tumours into hormone sensing and milk secreting cells based on the expression of transcription factors linked to cell identity (the luminal progenitor split), then split the hormone sensing group into luminal and apocrine groups based on oestrogen receptor activity (the luminal-apocrine split). I show that the luminal-apocrine-basal (LAB) approach can be applied to microarray data (186 tumours) from an EORTC trial and to RNA-seq data from TCGA (674 tumours), and compare results obtained with the LAB and PAM50 approaches. Unlike pure signature-based approaches, classification based on an explicit biological model has the advantage that it is both refutable and capable of meaningful improvement as biological understanding of mammary tumorigenesis improves.

cancer biology↗

bioRxiv2014

The disruption of trace element homeostasis due to aneuploidy as a unifying theme in the etiology of cancer

#### #### ABSTRACT FOR SCIENTISTS: While decades of cancer research have firmly established multiple hallmarks of cancer 1,2, cancers genomic landscape remains to be fully understood. Particularly, the phenomenon of aneuploidy gains and losses of large genomic regions, i.e. whole chromosomes or chromosome arms and why most cancer cells are aneuploid remains enigmatic 3. Another frequent observation in many different types of cancer is the deregulation of the homeostasis of the trace elements copper, zinc and iron. Concentrations of copper are markedly increased in cancer tissue and the blood plasma of cancer patients, while zinc levels are typically decreased 49. Here we discuss the hypothesis that the disruption of trace element homeostasis and the phenomenon of aneuploidy might be linked. Our tentative analysis of genomic data from diverse tumor types mainly from The Cancer Genome Atlas (TCGA) project suggests that gains and losses of metal transporter genes occur frequently and correlate well with transporter gene expression levels. Hereby they may confer a cancer-driving selective growth advantage at early and possibly also later stages during cancer development. This idea is consistent with recent observations in yeast, which suggest that through chromosomal gains and losses cells can adapt quickly to new carbon sources 10, nutrient starvation 11 as well as to copper toxicity 12. In human cancer development, candidate driving events may include, among others, the gains of zinc transporter genes SLC39A1 and SLC39A4 on chromosome arms 1q and 8q, respectively, and the losses of zinc transporter genes SLC30A5, SLC39A14 and SLC39A6 on 5q, 8p and 18q. The recurrent gain of 3q might be associated with the iron transporter gene TFRC and the loss of 13q with the copper transporter gene ATP7B. By altering cellular trace element homeostasis such events might contribute to the initiation of the malignant transformation. Intriguingly, attenuation or overexpression of several of these metal transporter genes has been shown to lead to malignant cellular behavior in vitro. Consistently, it has been shown that zinc affects a number of the observed hallmarks of cancer characteristics including DNA repair, inflammation and apoptosis, e.g. through its effects on NF-kappa B signaling. We term this model the aneuploidy metal transporter cancer (AMTC) hypothesis and find it compatible with the cancer-promoting role of point mutations and focal copy number alterations in established tumor suppressor genes and oncogenes (e.g. MYC, MYCN, TP53, PIK3CA, BRCA1, ERBB2). We suggest a number of approaches for how this hypothesis could be tested experimentally and briefly touch on possible implications for cancer etiology, metastasis, drug resistance and therapy. #### #### ABSTRACT FOR KIDS: We humans are made up of many very small building blocks, which are called cells. These cells can be seen with a microscope and they know how to grow and what to do from the information on the DNA of their chromosomes. Sometimes, if this information is messed up, a cell can go crazy and start to grow without control, even in places of the body where it should not. This process is called cancer, a terrible disease that makes people very sick. Scientists do not understand exactly what causes cells to go crazy, so it would be good to find out. Many years ago, scientists observed that chromosomes in these cancer cells are missing or doubled but could not find an explanation for it. More recently, scientists have detected that precious metals to our bodies, which are not gold and silver, but zinc, iron and copper, are not found in the right amounts in these crazy cancer cells. There seems to be not enough zinc and iron but too much copper, and again, scientists do not really understand why. So there are many unanswered questions about these crazy cancer cells and in this article, we describe a pretty simple idea on how chromosome numbers and the metals might be connected: we think that the missing or doubled chromosomes produce less or more transporters of zinc, iron and copper. As a result, cancer cells end up with little zinc and too much copper and these changes contribute to their out-of-control growth. If this idea were true, many people would be excited about it. But first this idea needs to be investigated more deeply in the laboratory, on the computer and in the hospitals. Therefore, we put it out on the internet so that other people can also think about and work on our idea. Now there are plenty of ways to do exciting experiments and with the results, we will hopefully understand much better why cancer cells go crazy and how doctors could improve their therapies to help patients in the future. #### #### ABSTRACT FOR ADULTS: One hundred years ago, it was suggested that cancer is a disease of the chromosomes, based on the observations that whole chromosomes or chromosome arms are missing or duplicated in the genomes of cells in a tumor. This phenomenon is called aneuploidy and is observed in most types of cancer, including breast, lung, prostate, brain and other cancers. However, it is not clear which genes could be responsible for this observation or if this phenomenon is only a side effect of cancer without importance, so it is important to find out. A second observation from basic research is that concentrations of several micronutrients, especially of the trace elements zinc, copper and iron are changed in tumor cells. In this article, we speculate that aneuploidy is the reason for these changes and that together, these two phenomena are responsible for some of the famous hallmarks or characteristics that are known from cancer cells: fast growth, escape from destruction by the immune system and poor DNA repair. This idea is new and has not been tested yet. We name it the aneuploidy metal transporter cancer (AMTC) hypothesis. To test our idea we used a wealth of information that was shared by international projects such as the Human Genome Project or the Cancer Genome Atlas Project. Indeed, we find that many zinc, iron and copper transporter genes in the genome are affected by aneuploidy. While a healthy cell has two copies of each gene, some tumor cells have only one or three copies of these genes. Furthermore, the amounts of protein and the activities of these metal transporters seem to correlate with these gene copy numbers, at least we see that the intermediate molecules and protein precursors called messenger RNA correlate well. Hence, we found that the public data is compatible with our suggested link between metal transporters and cancer. Furthermore, we identified hundreds of studies on zinc biology, evolutionary biology, genome and cancer research that also seem compatible. For example, cancer risk increases in the elderly population as well as in obese people, it also increases after certain bacterial or viral infections and through alcohol consumption. Consistent with the AMTC hypothesis and in particular, the idea that external changes in zinc concentrations in an organ or tissue may kick off the earliest steps of tumor development, all of these risk factors have been correlated with changes in zinc or other trace elements. However, since additional experiments to test the AMTC hypothesis have not yet been performed, direct evidence for our hypothesis is still missing. We hope, however, that our idea will promote further research with the goal to better understand cancer as a first step towards its prevention and the development of improved anti-cancer therapies in the future.

Cancer Biology↗

bioRxiv2018

ERK1/2-dependent activation of FCHSD2 drives cancer cell-selective regulation of clathrin-mediated endocytosis

Clathrin-mediated endocytosis (CME) regulates the uptake of cell surface receptors, as well as their downstream signaling activities. We recently reported that signaling reciprocally regulates CME in cancer cells and that the crosstalk can contribute to cancer progression. To further explore the nature and extent of the crosstalk between signaling and CME in cancer cell biology, we analyzed a panel of oncogenic signaling kinase inhibitors for their effects on CME. Inhibition of several kinases selectively affected CME function in cancer cells. Among these, ERK1/2 inhibition selectively inhibited CME in cancer cells by decreasing the rate of CCP initiation. We identified an ERK1/2 substrate, the FCH/F-BAR and SH3 domain-containing protein, FCHSD2, as being essential for the ERK1/2-dependent effects on CME and CCP initiation. ERK1/2 phosphorylation activates FCHSD2 and regulates EGFR endocytic trafficking as well as downstream signaling activities. Loss of FCHSD2 activity in non-small-cell lung cancer cells leads to increased cell surface expression and altered signaling downstream of EGFR, resulting in enhanced cell proliferation and migration. The expression level of FCHSD2 is positively correlated with higher cancer patient survival rate, suggesting that FCHSD2 negatively affects cancer progression. These findings provide new insight into the mechanisms and consequences of the reciprocal regulation of signaling and CME in cancer cells.\n\nSignificanceClathrin-mediated endocytosis (CME) determines the internalization of receptors and their downstream signaling. We discovered that CME is differentially regulated by specific signaling kinases in cancer cells. In particular, ERK1/2-mediated phosphorylation of the FCH/F-BAR and double SH3 domains-containing protein 2 (FCHSD2) regulates CME, and the trafficking and signaling activities of EGF receptors. This reciprocal interaction negatively regulates cancer proliferation and migration. The expression level of FCHSD2 is positively correlated with higher cancer patient survival rates. This study identifies signaling pathways that impinge on the endocytic machinery and reveals a molecular nexus for crosstalk between intracellular signaling and CME. Cancer cells specifically adapt this crosstalk as a determinant for tumor progression, which has implications for novel therapeutics against cancers.

cell biology↗

bioRxiv2018

Systems Biology Understanding of the Effects of Lithium on Cancer.

Lithium has many widely varying biochemical and phenomenological effects, suggesting that a systems biology approach is required to understand its action. Multiple lines of evidence point to lithium as a significant factor in development of cancer, showing that understanding lithium action is of high importance. In this paper we undertake first steps towards a systems approach by analyzing mutual enrichment between the interactomes of lithium-sensitive enzymes and the pathways associated with cancer. This work integrates information from two important databases, STRING and KEGG pathways. We find that for the majority of cancer pathways the mutual enrichment is many times greater than chance, reinforcing previous lines of evidence that lithium is an important influence on cancer.

cancer biology↗

bioRxiv2017

Quantifying Spontaneous Metastasis In A Syngeneic Mouse Melanoma Model Using Real Time PCR

Modeling metastasis in vivo with animals is a priority for both revealing mechanisms of tumor dissemination and developing therapeutic methods. While conventional intravenous injection of tumor cells provides an efficient and consistent system for studying tumor cell extravasation and colonization, studying spontaneous metastasis derived from orthotopic tumor sites has the advantage of modeling more aspects of the metastatic cascade, but is challenging as it is difficult to detect small numbers of metastatic cells. In this work, we developed an approach for quantifying spontaneous metastasis in the syngeneic mouse B16 system using real time PCR. We first transduced B16 cells with lentivirus expressing firefly luciferase Luc2 gene for bioluminescence imaging. Next, we developed a real time quantitative PCR (qPCR) method for the detection of luciferase-expressing, metastatic tumor cells in mouse lungs and other organs. To illustrate the approach, we quantified lung metastasis in both spontaneous and experimental scenarios using B16F0 and B16F10 cells in C57BL/6Ncrl and NOD-Scid Gamma (NSG) mice. We tracked B16 melanoma metastasis with both bioluminescence imaging and qPCR, which were found to be self-consistent. Using this assay, we can quantitatively detect one Luc2 positive tumor cells out of 104 tissue cells, which corresponds to a metastatic burden of 1.8x104 metastatic cells per whole mouse lung. More importantly, the qPCR method was at least a factor of 10 more sensitive in detecting metastatic cell dissemination and should be combined with bioluminescence imaging as a high-resolution, end-point method for final metastatic cell quantitation. Given the rapid growth of primary tumors in many mouse models, assays with improved sensitivity can provide better insight into biological mechanisms that underpin tumor metastasis.

cancer biology↗

bioRxiv2018

Imprint of parity and age at first birth on the genomic landscape of subsequent breast cancer

BackgroundAlthough parity and age at first birth are among the most known extrinsic factors that modulates breast cancer risk, their impact on the biology of subsequent breast cancer has never been explored in depth. In this study, we investigate the imprint of parity and age at first birth on the pattern of somatic mutations, somatic copy number alterations (SCNAs), transcriptomic profiles, and tumor infiltrating lymphocytes (TILs) levels of subsequent breast cancer.\n\nMethodsA total of 313 patients with primary breast cancer with available whole genome and RNA sequencing data were included in this study. We used a multivariate analysis adjusted for age at diagnosis, pathological stage, molecular subtypes and histological subtypes. We compared nulliparous vs. parous, late parous vs. early parous, and nulliparous vs. pregnancy associated breast cancer (PABC) patients. Late and early parous patients were grouped by using the median age at first birth as a cut-off value. PABC was defined as patients diagnosed up to 10 years postpartum.\n\nResultsGenomic alterations of breast cancer are associated with age at first birth but not parity status alone. Independently of clinicopathological features, early parous patients developed tumors characterized by a higher number of Indels (Padj = 0.002), a lower frequency of CDH1 mutations (1.2% vs. 12.7% Padj = 0.013), a higher frequency of TP53 mutations (50% vs. 22.5%; Padj = 0.010) and MYC amplification (28% vs. 7% Padj = 0.008), and a lower prevalence of mutational signature 2. PABC were associated with increased TILs infiltration (Padj = 0.0495).\n\nConclusionsThese findings highlight an unprecedented link between reproductive history and the genomic landscape of subsequent breast cancer. With the rapid development of precision oncology, this work advocates that reproductive history should not be underestimated in future clinical studies of breast cancer.

cancer biology↗

bioRxiv2018

Ensemble Feature Selection and Meta-Analysis of Cancer miRNA Biomarkers

The role of microRNAs (miRNAs) in cellular processes captured the attention of many researchers, since their dysregulation is shown to affect the cancer disease landscape by sustaining proliferative signaling, evading program cell death, and inhibiting growth suppressors. Thus, miRNAs have been considered important diagnostic and prognostic biomarkers for several types of tumors. Machine learning algorithms have proven to be able to exploit the information contained in thousands of miRNAs to accurately predict and classify cancer types. Nevertheless, extracting the most relevant miRNA expressions is fundamental to allow human experts to validate and make sense of the results obtained by automatic algorithms. We propose a novel feature selection approach, able to identify the most important miRNAs for tumor classification, based on consensus on feature relevance from high-accuracy classifiers of different typologies. The proposed methodology is tested on a real-world dataset featuring 8,129 patients, 29 different types of tumors, and 1,046 miRNAs per patient, taken from The Cancer Genome Atlas (TCGA) database. A new miRNA signature is suggested, containing the 100 most important oncogenic miRNAs identified by the presented approach. Such a signature is proved to be sufficient to identify all 29 types of cancer considered in the study, with results nearly identical to those obtained using all 1,046 features in the original dataset. Subsequently, a meta-analysis of the medical literature is performed to find references to the most important biomarkers extracted by the methodology. Besides known oncomarkers, 15 new miRNAs previously not ranked as important biomarkers for diagnosis and prognosis in cancer pathologies are uncovered. Such miRNAs, considered relevant by the machine learning algorithms, but still relatively unexplored by specialized literature, could provide further insights in the biology of cancer.

bioinformatics↗

bioRxiv2017

Pediatric Sarcoma Data Forms a Unique Cluster Measured via the Earth Mover’s Distance

In this note, we combined pediatric sarcoma data from Columbia University with adult sarcoma data collected from TCGA, in order to see if one can automatically discern a unique pediatric cluster in the combined data set. Using a novel clustering pipeline based on optimal transport theory, this turned out to be the case. The overall methodology may find uses for the classification of data from other biological networking problems.

cancer biology↗

bioRxiv2018

No effect of administration of unacylated ghrelin on subcutaneous PC3 xenograft growth in a Rag1-/- mouse model of metabolic dysfunction

Ghrelin is a peptide hormone which, when acylated, regulates appetite, energy balance and a range of other biological processes. Ghrelin predominately circulates in its unacylated form (unacylated ghrelin; UAG). UAG has a number of functions independent of acylated ghrelin, including modulation of metabolic parameters and cancer progression. UAG has also been postulated to antagonise some of the metabolic effects of acyl-ghrelin, including its effects on glucose and insulin regulation. In this study, Rag1-/- mice with high-fat diet-induced obesity and hyperinsulinaemia were subcutaneously implanted with PC3 prostate cancer xenografts to investigate the effect of UAG treatment on metabolic parameters and xenograft growth. Daily intraperitoneal injection of 100 g/kg UAG had no effect on xenograft tumour growth in mice fed normal rodent chow or 23% high-fat diet. UAG significantly improved glucose tolerance in host Rag1-/- mice on a high-fat diet, but did not significantly improve other metabolic parameters. We hypothesise that UAG is not likely to be an effective treatment for prostate cancer, with or without associated metabolic syndrome.\n\nConflict of interestThe authors declare no conflict of interest.

cancer biology↗

bioRxiv2015

Cancer classification in the genomic era: five contemporary problems

Classification is an everyday instinct as well as a full-fledged scientific discipline. Throughout the history of medicine, disease classification is central to how we develop knowledge, make diagnosis, and assign treatment. Here we discuss the classification of cancer, the process of categorizing cancer subtypes based on their observed clinical and biological features. Traditionally, cancer nomenclature is primarily based on organ location, e.g., \"lung cancer\" designates a tumor originating in lung structures. Within each organ-specific major type, finer subgroups can be defined based on patient age, cell type, histological grades, and sometimes molecular markers, e.g., hormonal receptor status in breast cancer, or microsatellite instability in colorectal cancer. In the past 15+ years, high-throughput technologies have generated rich new data regarding somatic variations in DNA, RNA, protein, or epigenomic features for many cancers. These data, collected for increasingly large tumor collections, have provided not only new insights into the biological diversity of human cancers, but also exciting opportunities to discover previously unrecognized cancer subtypes. Meanwhile, the unprecedented volume and complexity of these data pose significant challenges for biostatisticians, cancer biologists, and clinicians alike. Here we review five related issues that represent contemporary problems in cancer taxonomy and interpretation. 1. How many cancer subtypes are there? 2. How can we evaluate the robustness of a new classification system? 3. How are classification systems affected by intratumor heterogeneity and tumor evolution? 4. How should we interpret cancer subtypes? 5. Can multiple classification systems coexist? While related issues have existed for a long time, we will focus on those aspects that have been magnified by the recent influx of complex multi-omics data. Ongoing exploration of these problems is essential for data-driven refinement of cancer classification and the successful application of these concepts in precision medicine.

Genomics↗

bioRxiv2018

sigfit: flexible Bayesian inference of mutational signatures

Mutational signature analysis aims to infer the mutational spectra and relative exposures of processes that contribute mutations to genomes. Different models for signature analysis have been developed, mostly based on non-negative matrix factorisation or non-linear optimisation. Here we present sigfit, an R package for mutational signature analysis that applies Bayesian inference to perform fitting and extraction of signatures from mutation data. We compare the performance of sigfit to prominent existing software, and find that it compares favourably. Moreover, sigfit introduces novel probabilistic models that enable more robust, powerful and versatile fitting and extraction of mutational signatures and broader biological patterns. The package also provides user-friendly visualisation routines and is easily integrable with other bioinformatic packages.

cancer biology↗

bioRxiv2017

Immunologic Effect of Polysaccharides Extracted from Sipunculus nudus (SNP) on Hepatoma HepG2-bearing Mice

Since many studies have clarified the biological activity of polysaccharides, we investigated the effect of SNP which was the water-soluble polysaccharides extracted from Sipunculus nudus on Hepatoma HepG2-bearing Mice to verify the potential of SNP as an effective clinical agent for liver cancer therapy. SNP were administered at the doses of 50,100, and 200 mg/kg to HepG2-bearing mice to determine their antitumor effects. SNP had an inhibitory effect on the growth of HepG2 cells and enhanced the immunological effect on HepG2 tumor-bearing mice. SNP increased the expression of IL-2, IFN-{gamma}, and TNF- cytokines in serum, suggesting that SNP can strengthen the antitumor immune response. In addition, SNP increased ATF4, DDIT3, and IkB expression and decreased CYR61, HSP90, and VEGF expression, all of which are proteins involved in antitumor activity and cell death/survival. our results suggested that SNP may be a novel antitumor agent.\n\nSummary statementSNP(polysaccharides extracted from Sipunculus nudus) mediates anti-tumor activity through influencing immunoregulation, and SNP can be explored as a promising candidate for future anticancer drug.

cancer biology↗

bioRxiv2018

The ERBB-STAT3 Axis Drives Tasmanian Devil Facial Tumor Disease

The marsupial Tasmanian devil (Sarcophilus harrisii) faces extinction due to transmissible devil facial tumor disease (DFTD). To unveil the molecular underpinnings of DFTD, we designed an approach that combines sensitivity to drugs with an integrated systems-biology characterization. Sensitivity to inhibitors of the ERBB family of receptor tyrosine kinases correlated with their overexpression, suggesting a causative link. Proteomic and DNA methylation analyses revealed tumor-specific signatures linked to oncogenic signaling hubs including evolutionary conserved STAT3. Indeed, ERBB inhibition blocked phosphorylation of STAT3 and arrested cancer cells. Pharmacological blockade of ERBB signaling prevented tumor growth in a xenograft model and resulted in recovery of MHC class I gene expression. This link between the hyperactive ERBB-STAT3 axis and MHC class I mediated tumor immunosurveillance provides mechanistic insights into horizontal transmissibility and led us to the proposition of a dual chemo-immunotherapeutic strategy to save Tasmanian devils from DFTD.

cancer biology↗

bioRxiv2017

Clear Cell Renal Cell Carcinoma With Biallelic Inactivation Of CDKN2A/B On 9p21 Have Distinct Gene Expression Signature And Are Associated With Poor Prognosis

PurposeThe clinical implications of biallelic inactivation of CDKN2A/B in clear cell renal cell carcinoma (ccRCC) and relevant dysregulated biological pathways and gene signatures were investigated.\n\nMaterials and MethodsData were obtained from the TCGA data set and validated using Project GENIE and previously published dataset. CDKN2A/B allelic status was classified into 3 groups, including biallelic CDKN2A/B inactivation (homozygous deletion or combined heterozygous deletion and mutation), monoallelic CDKN2A/B loss (heterozygous deletion or mutation) and absent CDKN2A/B allelic loss. Univariate and multivariate cancer-specific survival and disease-free survival analyses were performed. Integrated analyses of copy number, gene expression (mRNA and miRNA), protein expression and methylation changes were conducted.\n\nResultsOf 440 patients with ccRCC 17 (3.9%) had biallelic CDKN2A/B inactivation and 116 (26.4%) had monoallelic CDKN2A/B loss. CDKN2A/B allelic inactivation was associated with late tumor stage, high histological grade, presence of metastasis and greater tumor size. Patients with biallelic deletion of CDKN2A/B showed significantly worse cancer-specific survival and disease-free survival (p<0.0001). Significant co-occurrence of MTAP homozygous deletion was observed in CDKN2A/B biallic inactivated tumors (46.7%; p<0.001). Significant underexpression of CDKN2A/B was observed in biallelic inactivated tumors at the mRNA and protein levels. miR-21 was the most highly expressed miRNA in biallelic inactivated tumors. Biallelic inactivated tumors were significantly enriched for genes related to activation of ATR in response to replication stress and miR-21 target genes.\n\nConclusionsCDKN2A/B biallelic inactivation may be a prognostic marker for ccRCC and is associated with distinct dysregulation of gene expression signatures.

cancer biology↗

bioRxiv2017

High accuracy label-free classification of kinetic cell states from holographic cytometry

Digital holographic microscopy permits live and label-free visualization of adherent cells. Here we report the application of this approach for high accuracy kinetic quantitative cytometry. We identify twenty-six label-free optical and morphological features that are biologically independent. When used as a basis for machine learning, these features allow blind single cell classification with up to 95% accuracy. We present methods to control for inherent holographic noise, thereby establishing a set of reliable quantitative features. Together, these contributions permit continuous digital holographic cytometry for three or more days. Applying our approach to human melanoma cells treated with a panel of cancer therapeutics, we can track the response of each cell, simultaneously classifying multiple behaviors such as cell cycle length, motility, apoptosis, senescence, and heterogeneity of response to each therapeutic. Importantly, we demonstrate relationships between these phenotypes over time. This work thus provides an experimental and computational roadmap for low cost live-cell imaging and kinetic classification of heterogeneous adherent cell populations.

cancer biology↗