La 7β-hydroxy-épiandrostérone, stéroïde endogène dérivant de la DHEA, présente des propriétés anti-inflammatoires. En effet, elle module la voie des prostaglandines (PGs) en inhibant la production de la PGE2 pro-inflammatoires et en augmentant la production de la 15-Deoxy-∆12,14-PGJ2 cyto-protectrice in vivo et in vitro. Les faibles doses de 7β-hydroxy-épiandrostérone (1nM, 10nM, 100nM) pour lesquelles ces effets sont observés, suggèrent une liaison à un récepteur spécifique. L’inflammation et la production des PGs jouent un rôle important dans le développement et la prolifération des tumeurs mammaires estrogéno-dépendantes. Le 17β-estradiol (E2), en se fixant sur les récepteurs des estrogènes (REs), induit la production de PGE2 et la prolifération cellulaire dans ces cellules tumorales. De ce fait, notre objectif était de tester les effets de la 7β-hydroxy-épiandrostérone sur la prolifération (comptage avec exclusion au bleu trypan), le cycle cellulaire et l’apoptose (cytométrie de flux) dans les lignées cellulaires de cancer du sein MCF-7 (REα+, REβ+, GPR30+) et MDA-MB-231 (REα-, REβ+, GPR30+) et d’identifier une(des) cible(s) potentielle(s) dans ces cellules (transactivation) et dans des cellules négatives pour les REs nucléaires SKBr3 (GPR30+) (études de prolifération). Cette étude a montré que la 7β-hydroxy-épiandrostérone exerce des effets anti-estrogéniques dans les cellules MCF-7 et MDA-MB-231 associés à une inhibition de la prolifération et un arrêt du cycle cellulaire. Les études de transactivation et de prolifération avec les agonistes spécifiques des REs ont montré une interaction avec le REβ. De plus, les résultats des études de proliférations sur les trois lignées cellulaires suggèrent que la 7β-hydroxy-épiandrostérone pourrait également interagir avec le GPR30. Ces résultats indiquent que ce stéroïde androgène agit comme un anti-estrogène. De plus, c’est la première fois qu’un stéroïde androgène à faible dose montre une action anti-proliférative dans des lignées de cancers du sein. Des études ultérieures restent à réaliser afin de mieux comprendre ces effets observés. / 7β-hydroxy-epiandrosterone, an endogenous androgenic derivative of DHEA, has previously been shown to exert anti-inflammatory action in vitro and in vivo via a shift from prostaglandin E2 (PGE2) to 15-deoxy-∆12,14-PGJ2 production. This modulation in prostaglandin production was obtained with low concentrations of 7β-hydroxy-epiandrosterone (1–100 nM) and suggested that it might act through a specific receptor. Inflammation and prostaglandin synthesis is important in the development and survival of estrogen-dependent mammary cancers. Estrogen induced PGE2 production and cell proliferation via its binding to estrogen receptors (ERs) in these tumors. Our objective was to test the effects of 7β-hydroxy-epiandrosterone on the proliferation (by counting with trypan blue exclusion), cell cycle and cell apoptosis (by flow cytometry) of breast cancer cell lines MCF-7 (ERα+, ERβ +, G-protein coupled receptor 30 : GPR30+) and MDA-MB-231 (ERα-, ERβ +, GPR30+) and to identify a potential target of this steroid in these cell lineages (by transactivations) and in the nuclear ER-negative SKBr3 cells (GPR30+) (by proliferation assays). 7β-hydroxy-epiandrosterone exerted anti-estrogenic effects in MCF-7 and MDA-MB-231 cells associated with cell proliferation inhibition and cell cycle arrest. Moreover, transactivation and proliferation with ER agonists assays indicated that 7β-hydroxy-epiandrosterone interacted with ERβ. Data from proliferation assays on the MCF-7, MDA-MB-231 and SKBr3 cell lines suggested that 7β-hydroxy-epiandrosterone may also act through the membrane GPR30 receptor.These results support that this androgenic steroid acts as an anti-estrogenic compound. Moreover, this is the first evidence that low doses of androgenic steroid exert antiproliferative effects in these mammary cancer cells. Further investigations are needed to improve understanding of the observed actions of endogenous 7β-hydroxy-epiandrosterone.

Made available in DSpace on 2014-08-20T13:32:50Z (GMT). No. of bitstreams: 1 dissertacao_natalia_camacho.pdf: 752258 bytes, checksum: 4db6bde27e4ad1a1adedd5d44779d4aa (MD5) Previous issue date: 2007-06-01 / Lectins are proteins or glicoproteins of non-immune origin with binding specificities for carbohidrates, that interact with glicocomponents present in plant and animal cells, bacteria and viruses. This property makes lectins remarkable markers used in histochemical and biochemical studies, and for characterization and differentiation of cells. Leguminous plants are the major source of lectins, proteins that possess important biological activities, like insecticidal and antiproliferative against cancer cell lines. Thus, the aim of this work was to develop a heterologous expression system for a recombinant lectin from Bauhinia forficata, a leguminous plant popularly known as pata-de-vaca , in E. coli, to study its characteristics and biological activities. The lectin gene bfl was amplified by PCR from genomic DNA, and cloned to expression vectors pQE30 e pET32a(+). Recombinant BFL was expressed in E. coli in insoluble form by using the vector pET32a(+)/bfl. The lectin was purified by Ni +2 -Sepharose affinity chromatography, with a yield of 40 mg.L -1 . The sequence and carbohidrate specificity of rBFL is similar to other related lectins. The rBFL lectin presents in monomer and dimer forms, with aparent molecular mass of 44 and 94 kDa, respectively, shows biological activity in hemagglutination assay in the presence of divalent metal cations (Ca +2 and Mn +2 ) and antiproliferative effect on human cancer cell lines MCF-7 (breast cancer), HT-29 (colon cancer) and HL-60 (leukemia) according as the concentration used. The rBFL lectin showed dose-dependent inhibition in HT-29 cells, stimulatory effect on proliferation of MCF-7 cells in higher concentrations, and no induction of cell death was observed in any cancer cell line. The results obtained in this work, about rBFL lectin, never before isolated or produced in heterologous system, motivates the performance of new characterization assays to elucidate possible applications. / Lectinas são proteínas ou glicoproteínas de origem não imune com propriedade de ligação especifíca a carboidratos, capazes de interagir com glicocomponentes presentes em células de plantas, animais, bactérias e vírus. Essa propriedade faz das lectinas notáveis marcadores utilizados em estudos histoquímicos, bioquímicos e na caracterização e diferenciação de células. Plantas leguminosas constituem-se na maior fonte de lectinas, que possuem atividades biológicas importantes, como atividade inseticida e antiproliferativa sobre células tumorais. Diante disto, o objetivo deste trabalho foi desenvolver um sistema de expressão heteróloga para uma lectina de Bauhinia forficata (rBFL), popularmente conhecida como pata-de-vaca , em E. coli, com o intuito de elucidar suas características e atividades biológicas. O gene bfl da lectina foi amplificado por PCR a partir do DNA genômico, e clonado nos vetores de expressão pQE30 e pET32a(+). A lectina rBFL foi expressa em larga escala pelo vetor pET32a(+)/bfl em E. coli, na forma insolúvel. A purificação foi realizada por cromatografia de afinidade em coluna de Ni +2 -Sepharose, com rendimento de 40 mg.L -1 . A seqüência da lectina rBFL e sua especificidade por carboidrato é similar a de lectinas relacionadas. A lectina rBFL apresenta-se na forma de monômeros e dímeros, com massa molecular aparente de 44 e 94 kDa, respectivamente, possui atividade biológica em ensaio de hemaglutinação na presença de cátions divalentes (Ca +2 and Mn +2 ) e demonstra efeito antiproliferativo sobre as linhagens tumorais humanas MCF-7 (câncer de mama), HT-29 (câncer de cólon) e HL-60 (leucêmica), dependendo da concentração utilizada. A rBFL demonstrou efeito inibitório dose-dependente sobre HT-29, e efeito estimulatório sobre a proliferação da linhagem MCF-7 em altas concentrações, não induzindo morte celular em nenhuma das linhagens. Os resultados obtidos neste trabalho acerca da rBFL, nunca antes isolada ou produzida em sistema heterólogo, motivam a realização de novos ensaios de caracterização visando possíveis aplicações.

Cancer cells have been known for some time to have very different metabolismas compared to that of normal non proliferating cells. As metabolism is involvedin almost every aspect of cell function, there has been a recent resurgence ofinterest in inhibiting cancer metabolism as a therapeutic strategy. Inhibitors thatspecifically target altered metabolic components in cancer cells are being developedas antiproliferative agents. However, many such inhibitors have not progressedinto the clinic due to limited efficacy either in vitro or in vivo. In this study weexplore the hypothesis that this is often due to the robustness of the metabolicnetwork and the differences between individual cancer cell lines in their metaboliccharacteristics. We take a systems biology approach. We investigate the cellular bioenergetic profiles of a panel of five non-small celllung cancer cell lines before and after treatment with a novel inhibitor of theglutaminase-1 (GLS1) enzyme. Additionally, we explore the effects of this inhibitoron intracellular metabolism of these cell lines as well as on the uptake and secretionof glucose, lactate and amino acids. To be able to do the latter robustly, wehad to modify the experimental assay considerably from procedures that seemto be standard in the literature; using these earlier procedures the metabolicenvironment of the cells was highly variable, leading to misleading results onthe metabolic effects of the inhibitor. We reduced cell density, altered mediumvolume and changed the time-window of the assay. This led to the cells growingexponentially, appearing indifferent to the few remaining changes. In this newassay, the metabolic effects of the glutaminase inhibitor became robust. One of the most significant results of this study is the metabolic heterogeneitydisplayed across the cell line panel under basal conditions. Differences in themetabolic functioning of the cell lines were observed in terms of both theirbioenergetic and metabolic profile. The amount of respiration attributed tooxidative phosphorylation differed between cell lines and respiratory capacity wasattenuated in most cells. However, the rate of glycolysis was similar betweencell lines in this assay. These results suggest that the Warburg effect arisesthrough a greater diversity of mechanisms than traditionally assumed, involvingvarious combinations of changes in the expression of glycolytic and mitochondrialmetabolic enzymes. The effects of GLS1 inhibition on cellular bioenergetics and metabolism alsodiffered between cell lines, even between resistant cell lines, indicating that theremay also be a diversity of resistance mechanisms. The metabolomic response ofcell lines to treatment suggests potential resistance mechanisms through metabolicadaptation or through the prior differences in the metabolic function of resistantcell lines. Part of the metabolome response to GLS1 inhibition was quite specificfor sensitive cells, with high concentrations of IMP as the strongest marker. Our results suggest that the metabolome is a significant player in what determinesthe response of cells to metabolic inhibitors, that its responses differ between cancercells, that responses are not beyond systems understanding, and that thereforethe metabolome should be taken into account in the design of and therapy withanti-cancer drugs.

Objectives: To investigate the effects of serotonin and melatonin (MLT) on the regulation of malignant growth and the activity of serotonin receptors (5HTR1a/-1b) in prostate cancer (PCa) cell lines. Materials and Methods: In four PCa cell lines (LNCaP, 22RV1, PC3, DU145) and two reference cell lines 5HTR1a and -1b, relative mRNA expression levels were assessed. Different serotonin and MLT receptor agonists and antagonists were used in stimulation and inhibition experiments. Results: mRNA expression of 5HTR1b was higher than that of 5HTR1a in all PCa cell lines. Serotonin showed a significant growth stimulatory effect in all PCa lines. The 5HTR1a and -1b agonists/antagonists did not significantly affect viability. MLT inhibited viability only in PC3 cells. Similarly, the 5HTR1a antagonist induced apoptotic changes in PC3 cells only at 10–4M, while the 5HTR1b antagonist induced necrosis at 10–4M in all cell lines. Cell cycle alterations were seen in PC3 and DU145 cells under the influence of the 5HTR1a antagonist. Conclusions: Serotonin receptor antagonists and agonists as well as MLT influence viability and apoptosis of PCa cell lines at supraphysiologic concentrations. In contrast to other reports, our results do not support a regulatory role of serotonin or MLT receptor activation or inhibition in PCa growth. / Dieser Beitrag ist mit Zustimmung des Rechteinhabers aufgrund einer (DFG-geförderten) Allianz- bzw. Nationallizenz frei zugänglich.

Devant le grand nombre de tumeurs du sein triple négatif résistant aux traitements, il est essentiel de comprendre les mécanismes de résistance et de trouver de nouvelles molécules efficaces. En premier lieu, nous analysons deux ensembles de données pharmacogénomiques à grande échelle. Nous proposons une nouvelle classification basée sur des profils transcriptomiques de lignées cellulaires, selon un processus de sélection de gènes basé sur des réseaux biologiques. Notre classification moléculaire montre une plus grande homogénéité dans la réponse aux médicaments que lorsque l’on regroupe les lignées cellulaires en fonction de leur tissu d'origine. Elle permet également d’identifier des profils similaires de réponse aux traitements. Dans un second travail, nous étudions une cohorte de patients atteints d’un cancer du sein triple négatif ayant résisté à la chimiothérapie néoadjuvante. Nous effectuons des analyses moléculaires complètes basées sur du RNAseq et WES. Nous constatons une forte hétérogénéité moléculaire des tumeurs avant et après traitement. Bien que nous observons une évolution clonale sous traitement, aucun mécanisme récurrent de résistance n’a pu être identifié. Nos résultats suggèrent fortement que chaque tumeur a un profil moléculaire unique et qu'il est important d'étudier de grandes séries de tumeurs. Enfin, nous améliorons une méthode pour tester la surreprésentation de motifs connus de protéines de liaison à l'ARN, dans un ensemble donné de séquences régulées. Cet outil utilise une approche innovante pour contrôler la proportion de faux positifs qui n'est pas réalisé par l'algorithme existant. Nous montrons l'efficacité de notre approche en utilisant deux séries de données différentes. / Given the large number of treatment-resistant triple-negative breast cancers, it is essential to understand the mechanisms of resistance and to find new effective molecules. First, we analyze two large-scale pharmacogenomic datasets. We propose a novel classification based on transcriptomic profiles of cell lines, according to a biological network-driven gene selection process. Our molecular classification shows greater homogeneity in drug response than when cell lines are grouped according to their original tissue. It also helps identify similar patterns of treatment response. In a second analysis, we study a cohort of patients with triple-negative breast cancer who have resisted to neoadjuvant chemotherapy. We perform complete molecular analyzes based on RNAseq and WES. We observe a high molecular heterogeneity of tumors before and after treatment. Although we highlighted clonal evolution under treatment, no recurrent mechanism of resistance could be identified Our results strongly suggest that each tumor has a unique molecular profile and that that it is increasingly important to have large series of tumors. Finally, we are improving a method for testing the overrepresentation of known RNA binding protein motifs in a given set of regulated sequences. This tool uses an innovative approach to control the proportion of false positives that is not realized by the existing algorithm. We show the effectiveness of our approach using two different datasets.

In this recent study,1 the authors analyzed the metabolic gene essentiality scores from genome-wide loss of function CRISPR screens in 769 human cancer cell lines and noticed that TCA cycle-associated genes clustered in two separate groups: one forming the traditional TCA cycle and another related to a non-canonical TCA cycle module. They monitored both modules with elegant tracing studies using [U-13C]glucose which generates citrate labeled with two 13C atoms (M+2).

The thesis deals with the natural substances in context with the cancer disease. The natural substances have a positive effect on the human organism and they are able to influence the viability and the growth of the cancer cells. The main mechanical device is to influence the mechanisms needed to start the apoptosis of the cancer cells and stopping further proliferation. The cancer cell lines utilization in the cancer disease is discussed in the thesis too. The thesis states common methods of determining the natural substances cytotoxicity. For the experimental part of the thesis it was chosen the MTT test method and the xCELLigence system for monitoring in real time. The mechanical device of the tested substance capsaicin in application on the prostate cell lines, tumorous PC3 and nontumorous PNT1A influence will be observed within the experimental part of the thesis.

Despite advances in cancer diagnosis and therapy, cancer is the second leading cause of death globally. The improvements of cancer treatment are the major challenge in this research. The aim of the thesis was studying of effects of two anticancer drugs ellipticine (Elli) and doxorubicin (DOX) on some cancer and healthy cell lines. Specific consideration was given to expand current knowledge about the metabolism and cytostatic effects of Elli in neuroblastoma cell lines. Another part of this study was focused on mechanisms contributing to the development of ellipticine-resistance in cancer cells and influence of histone deacetylase inhibitors on anticancer therapy was investigated. Moreover, the aim was to develop apoferritin (Apo) nanocarrier suitable for the active transport of cytostatics to cancer cells. Several essential data were found in this doctoral thesis. Anticancer efficiency of Elli depends on the CYP3A4-mediated metabolism in cancer. The CYP3A4 enzyme encapsulated into two nanoparticle forms, liposomes and SupersomesTM , was tested to activate ellipticine to its reactive species forming covalent DNA adducts. The formation of adducts seems to be dependent on concentrations of CYP3A4 in nanoparticle systems. A higher effectiveness of CYP3A4 in SupersomesTM than in liposomes to form...

Das Harnblasenkarzinom (BCa) ist die zweithäufigste bösartige urologische Tumorerkrankung sowie die siebthäufigste tumorbedingte Todesursache bei Männern. Zur Senkung des erheblichen Rezidiv- und Progressionsrisikos oberflächlicher BCa kommen lokale Immun- oder Chemotherapeutika zum Einsatz, die jedoch starke Nebenwirkungen verursachen können bzw. ungenügende langfristige Effekte bewirken. Eine neuartige Therapieoption besteht in der gezielten Expressionshemmung von Genen, die den Tumorzellen einen Wachstumsvorteil vermitteln. Hierfür eignen sich besonders synthetische Nukleinsäuren wie Antisense-Oligodesoxynukleotide (AS-ODN) und small interfering RNAs (siRNAs). In der vorliegenden Arbeit wurde die Expressionshemmung des potenziellen Targetgens hTERT (humane Telomerase Reverse Transkriptase) mit AS-ODN und siRNAs in BCa-Zellen untersucht. Die Tumorspezifität der hTERT-mRNA-Expression konnte zunächst an tumor- und tumorfreien Gewebeproben von BCa-Patienten gezeigt werden. Die verwendeten AS-ODN reduzierten die hTERT-mRNA-Expression auf bis zu 40%, womit eine Verringerung der Telomeraseaktivität einherging. Die AS-ODN-Behandlung bewirkte des Weiteren eine konzentrationsabhängige Viabilitätsreduktion verschiedener BCa-Zelllinien sowie eine verminderte Zellkoloniebildungsrate. Diese antiproliferativen Effekte waren auf eine Apoptoseinduktion zurückzuführen. Durch eine Vorbehandlung von vier BCa-Zelllinien mit hTERT-AS-ODN konnten die zytotoxischen Effekte der für das BCa relevanten Chemotherapeutika Cisplatin, Mitomycin C und Gemcitabin signifikant verstärkt werden. Nach Untersuchung der AS-ODN-Wirkung in vitro erfolgte die Etablierung eines subkutanen Xenotransplantantmodells der Nacktmaus. Die Eignung einer intraperitonealen Applikation wurde mit fluoreszenzmarkierten AS-ODN belegt. In weiteren Zellkulturexperimenten kamen hTERT-siRNAs, als alternative Methode der Geninhibition, zum Einsatz. Die Reduktion der hTERT-mRNA-Expression auf 50% war mit der durch AS-ODN bewirkten Inhibition vergleichbar. Im Gegensatz zur AS-ODN-Behandlung induzierten siRNAs keine unmittelbare Apoptose. Eine Kombination der siRNAs mit Cisplatin und Mitomycin C bewirkte jedoch eine Verdopplung der Apoptoserate. Um die molekularen Mechanismen der Wirkung der nukleinsäurebasierten hTERT-Inhibitoren und den Einfluss targetunabhängiger Effekte zu untersuchen, wurden transkriptomweite Expressionsanalysen mittels Oligonukleotid-Microarrays durchgeführt. Hierbei zeigte sich, dass die AS-ODN-Behandlung vorwiegend zu einer gesteigerten Expression von Genen führte, die mit einer zellulären Stressantwort assoziiert sind (u.a. ATF3, EGR1, GADD45). Diese Expressionsmuster stimmten in hohem Maße mit denen überein, die durch Transfektion mit AS-ODN gegen andere Targets erhalten wurden. Diese Ergebnisse deuten auf eine, zumindest teilweise, durch off-Targeteffekte ausgelöste Wachstumshemmung hin. Die siRNA-Behandlungen gegen unterschiedliche Targets zeigten relativ geringe Übereinstimmungen in den Expressionsmustern und somit eine höhere Spezifität. Außerdem wurde erstmalig gezeigt, dass eine hTERT-Inhibition mit siRNAs zur trankriptionellen Hemmung der Onkogene EGFR und FOSL1 führt. Diese Daten sowie die Ergebnisse anderer Arbeitsgruppen deuten auf einen wechselseitigen Zusammenhang zwischen hTERT und EGFR in der Regulation der EGFR-stimulierten Proliferation von BCa-Zellen hin. Zusammenfassend lässt sich feststellen, dass hTERT als tumorspezifisch exprimierter und funktionell relevanter Faktor ein hervorragendes Target für eine nukleinsäurebasierte BCa-Therapieoption darstellt. Im Vergleich zu AS-ODN wirken siRNAs grundsätzlich targetspezifischer. Die therapeutische Wertigkeit der lokal applizierten Inhibitoren, insbesondere in Kombination mit herkömmlichen Chemotherapeutika, sollte in nachfolgenden Experimenten im Rahmen eines orthotopen BCa-Xenotransplantatmodells untersucht werden.

Auf die Entwicklung der Hochdurchsatz-Sequenzierung (HTS) folgte eine Reihe von speziellen Erweiterungen, die erlauben verschiedene zellbiologischer Aspekte wie Genexpression, DNA-Methylierung, etc. zu messen. Die Analyse dieser Daten erfordert die Entwicklung von Algorithmen, die einzelne Experimenteberücksichtigen oder mehrere Datenquellen gleichzeitig in betracht nehmen. Der letztere Ansatz bietet besondere Vorteile bei Analyse von einzelligen RNA-Sequenzierung (scRNA-seq) Experimenten welche von besonders hohem technischen Rauschen, etwa durch den Verlust an Molekülen durch die Behandlung geringer Ausgangsmengen, gekennzeichnet sind. Um diese experimentellen Defizite auszugleichen, habe ich eine Methode namens netSmooth entwickelt, welche die scRNA-seq-Daten entrascht und fehlende Werte mittels Netzwerkdiffusion über ein Gennetzwerk imputiert. Das Gennetzwerk reflektiert dabei erwartete Koexpressionsmuster von Genen. Unter Verwendung eines Gennetzwerks, das aus Protein-Protein-Interaktionen aufgebaut ist, zeige ich, dass netSmooth anderen hochmodernen scRNA-Seq-Imputationsmethoden bei der Identifizierung von Blutzelltypen in der Hämatopoese, zur Aufklärung von Zeitreihendaten unter Verwendung eines embryonalen Entwicklungsdatensatzes und für die Identifizierung von Tumoren der Herkunft für scRNA-Seq von Glioblastomen überlegen ist. netSmooth hat einen freien Parameter, die Diffusionsdistanz, welche durch datengesteuerte Metriken optimiert werden kann. So kann netSmooth auch dann eingesetzt werden, wenn der optimale Diffusionsabstand nicht explizit mit Hilfe von externen Referenzdaten optimiert werden kann. Eine integrierte Analyse ist auch relevant wenn multi-omics Daten von mehrerer Omics-Protokolle auf den gleichen biologischen Proben erhoben wurden. Hierbei erklärt jeder einzelne dieser Datensätze nur einen Teil des zellulären Systems, während die gemeinsame Analyse ein vollständigeres Bild ergibt. Ich entwickelte eine Methode namens maui, um eine latente Faktordarstellungen von multiomics Daten zu finden. / The development of high throughput sequencing (HTS) was followed by a swarm of protocols utilizing HTS to measure different molecular aspects such as gene expression (transcriptome), DNA methylation (methylome) and more. This opened opportunities for developments of data analysis algorithms and procedures that consider data produced by different experiments. Considering data from seemingly unrelated experiments is particularly beneficial for Single cell RNA sequencing (scRNA-seq). scRNA-seq produces particularly noisy data, due to loss of nucleic acids when handling the small amounts in single cells, and various technical biases. To address these challenges, I developed a method called netSmooth, which de-noises and imputes scRNA-seq data by applying network diffusion over a gene network which encodes expectations of co-expression patterns. The gene network is constructed from other experimental data. Using a gene network constructed from protein-protein interactions, I show that netSmooth outperforms other state-of-the-art scRNA-seq imputation methods at the identification of blood cell types in hematopoiesis, as well as elucidation of time series data in an embryonic development dataset, and identification of tumor of origin for scRNA-seq of glioblastomas. netSmooth has a free parameter, the diffusion distance, which I show can be selected using data-driven metrics. Thus, netSmooth may be used even in cases when the diffusion distance cannot be optimized explicitly using ground-truth labels. Another task which requires in-tandem analysis of data from different experiments arises when different omics protocols are applied to the same biological samples. Analyzing such multiomics data in an integrated fashion, rather than each data type (RNA-seq, DNA-seq, etc.) on its own, is benefitial, as each omics experiment only elucidates part of an integrated cellular system. The simultaneous analysis may reveal a comprehensive view.