| 1. |
- Bernardo, Carina, et al.
(author)
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Molecular pathology of the luminal class of urothelial tumors
- 2019
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In: Journal of Pathology. - : Wiley. - 0022-3417 .- 1096-9896. ; 249:3, s. 308-318
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Journal article (peer-reviewed)abstract
- Molecular subtypes of urothelial carcinoma may be divided into luminal and nonluminal tumors. Nonluminal tumors are composed of cases with basal/squamous-like or small cell/neuroendocrine features, with a consensus on the molecular characteristics of the respective subtype. In contrast, luminal tumors are more disparate with three to five suggested subtypes and with definitions that do not always cohere. To resolve some of these disparities we assembled a cohort of 344 luminal tumors classified as urothelial-like (Uro), with the subtypes UroA, UroAp, UroB, and UroC, or genomically unstable (GU) according to the LundTax system. Cases were systematically analyzed by immunohistochemistry using antibodies for proteins representing important biological processes or cellular states: KRT5, EGFR, and CDH3 for the integrity of a basal cell layer; CCNB1, Ki67, and FOXM1 for proliferation; FGFR3 and ERBB2 for receptor tyrosine kinase status; CCND1, CDKN2A(p16), RB1, and E2F3 for cell cycle regulation; PPARG, GATA3, and TP63 for the differentiation regulatory system; and KRT20 and UPK3 for the differentiation readout. We show that Uro tumors form one, albeit heterogenous, group characterized by FGFR3, CCND1, and RB1 expression, but low or absence of CDKN2A(p16) and ERBB2 expression. The opposite expression pattern is observed in GU cases. Furthermore, Uro tumors are distinguished from GU tumors by showing a high RB1/p16 expression ratio. Class defining characteristics were independent of pathological stage and growth pattern, and thus intrinsic. In Uro tumors, proliferation was limited to a well-defined single layer of basal-like cells in UroA tumors but occurred throughout the tumor parenchyma, independent of the basal layer, in the more progressed UroAp and UroC tumors. A similar change in proliferation topology was not observed in GU. We conclude that luminal urothelial carcinomas consist, at the molecular pathology level, of two major subtypes, the larger heterogenous Uro and the biologically distinct GU subtype.
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| 2. |
- Bernardo, Carina, et al.
(author)
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Molecular pathology of the non-luminal Ba/Sq-like and Sc/NE-like classes of urothelial tumours : An integrated immunohistochemical analysis
- 2022
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In: Human Pathology. - : Elsevier BV. - 0046-8177. ; 122, s. 11-24
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Journal article (peer-reviewed)abstract
- Several groups have during past years produced molecular classification schemes for bladder cancer. Even though no consensus on how to define a subtype exists, one approach has been to base definitions on how tumours cluster according to their mRNA expression profiles. In many cases, obtained profiles, and thus class defining features, are affected by signals from non-tumour cells within the biopsy. To overcome this issue, we combined gene expression analyses with analyses of the actual tumour cells by extensive immunohistochemistry (IHC). By this approach we were able to define tumour cell phenotypes i.e., subtypes defined by features of the tumour cells only, and adjust mRNA-based algorithms accordingly. In the present investigation we address the non-luminal Basal/Squamous-like (Ba/Sq) and Small cell/Neuroendocrine-like (Sc/NE) categories of tumours defined by mRNA-based classification. We make use of IHC data for 15 proteins, all known to be instrumental for defining molecular subtypes of urothelial carcinoma. We show that the UroB type of tumours, frequently grouped together with Ba/Sq, are different from the Ba/Sq entity at several essential features and is a derivative of Urothelial-like tumours (Uro). We show that the Sc/NE tumours are similar to but represents extreme versions of Genomically Unstable (GU) tumours. We apply clustering to 423 cases representing all subtypes using IHC data for 14 proteins and show that the obtained grouping conforms well with the mRNA-based classification. This work describes in detail the molecular pathology of non-luminal RNA-based bladder cancer subtypes and highlight similarities/dissimilarities suggestive of origin.
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| 3. |
- Bocci, Matteo, et al.
(author)
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Activin receptor-like kinase 1 is associated with immune cell infiltration and regulates CLEC14A transcription in cancer
- 2019
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In: Angiogenesis. - : Springer Science and Business Media LLC. - 0969-6970 .- 1573-7209. ; 22:1, s. 117-131
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Journal article (peer-reviewed)abstract
- Cancer cells sustain their metabolic needs through nutrients and oxygen supplied by the bloodstream. The requirement for tumor angiogenesis has been therapeutically exploited in the clinical setting mainly by means of inhibition of the vascular endothelial growth factor family of ligands and receptors. Despite promising results in preclinical models, the benefits for patients proved to be limited. Inadequate efficacy similarly halted the development of agents impinging on the activity of the activin receptor-like kinase (ALK)1, a member of the transforming growth factor-β superfamily. Notwithstanding its characterization as an endothelial cell marker, the full spectrum of biological processes associated with ALK1 is essentially unexplored. Here, we present data revealing the genetic network associated with ACVRL1 (the gene encoding for ALK1) expression in human cancer tissues. Computational analysis unveiled a hitherto unknown role for ACVRL1 in relation to genes modulating the functionality of the immune cell compartment. Moreover, we generated a signature of 8 genes co-expressed with ACVRL1 across different tumor types and characterized the c-type lectin domain containing protein (CLEC)14A as a potential downstream target of ACVRL1. Considering the lack of reagents for ALK1 detection that has hampered the field to date, our work provides the opportunity to validate the 8-gene signature and CLEC14A as biomarkers for ALK1 activity. Ultimately, this may help revisit the clinical development of already existing ALK1-blocking compounds as precision medicines for cancer.
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| 4. |
- Eriksson, Pontus, et al.
(author)
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A comparison of rule-based and centroid single-sample multiclass predictors for transcriptomic classification
- 2022
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In: Bioinformatics. - : Oxford University Press (OUP). - 1367-4803 .- 1367-4811. ; 38:4, s. 1022-1029
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Journal article (peer-reviewed)abstract
- MOTIVATION: Gene expression-based multiclass prediction, such as tumor subtyping, is a non-trivial bioinformatic problem. Most classifier methods operate by comparing expression levels relative to other samples. Methods that base predictions on the expression pattern within a sample have been proposed as an alternative. As these methods are invariant to the cohort composition and can be applied to a sample in isolation, they can collectively be termed single sample predictors (SSP). Such predictors could potentially be used for preprocessing-free classification of new samples and be built to function across different expression platforms where proper batch and dataset normalization is challenging. Here we evaluate the behavior of several multiclass single sample predictors based on binary gene-pair rules (k-Top Scoring Pairs, Absolute Intrinsic Molecular Subtyping, and a new Random Forest approach) and compare them to centroids built with centered or raw expression values, with the criteria that an optimal predictor should have high accuracy, overcome differences in tumor purity, be robust across expression platforms, and provide an informative prediction output score.RESULTS: We found that gene-pair based SSPs showed excellent performance on many expression-based classification tasks. The three methods differed in prediction score output, handling of tied scores, and behavior in low purity samples. The k-Top Scoring Pairs and Random Forest approach both achieved high classification accuracy while providing an informative prediction score. Although gene-pair-based SSPs have been touted as being cross-platform compatible (through training on mixed platform data), out-of-the-box compatibility with a new dataset remains a potential issue that warrants cohort-to-cohort verification.AVAILABILITY: Our R package 'multiclassPairs' (https://cran.r-project.org/package=multiclassPairs) (https://doi.org/10.1093/bioinformatics/btab088) is freely available and enables easy training, prediction, and visualization using the gene-pair rule-based Random Forest SSP method and provides additional multiclass functionalities to the switchBox k-Top-Scoring Pairs package.SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
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| 5. |
- Hurst, Carolyn D., et al.
(author)
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Stage-stratified molecular profiling of non-muscle-invasive bladder cancer enhances biological, clinical, and therapeutic insight
- 2021
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In: Cell Reports Medicine. - : Elsevier BV. - 2666-3791. ; 2:12
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Journal article (peer-reviewed)abstract
- Understanding the molecular determinants that underpin the clinical heterogeneity of non-muscle-invasive bladder cancer (NMIBC) is essential for prognostication and therapy development. Stage T1 disease in particular presents a high risk of progression and requires improved understanding. We present a detailed multi-omics study containing gene expression, copy number, and mutational profiles that show relationships to immune infiltration, disease recurrence, and progression to muscle invasion. We compare expression and genomic subtypes derived from all NMIBCs with those derived from the individual disease stages Ta and T1. We show that sufficient molecular heterogeneity exists within the separate stages to allow subclassification and that this is more clinically meaningful for stage T1 disease than that derived from all NMIBCs. This provides improved biological understanding and identifies subtypes of T1 tumors that may benefit from chemo- or immunotherapy.
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| 6. |
- Jakobsson, Lovisa, et al.
(author)
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Low Frequency of Intratumor Heterogeneity in Bladder Cancer Tissue Microarrays
- 2018
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In: Bladder Cancer. - 2352-3727. ; 4:3, s. 327-337
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Journal article (peer-reviewed)abstract
- Background: Intratumoral heterogeneity (ITH) is associated with clinical challenges such as possible differences in response to treatment and difficulties in classifying the tumor. Previously, ITH has been described in bladder cancer using detailed genetic analyses. However, in this disease, it is not known to what extent ITH actually occurs, or if it involves molecular subtyping, when assessment is achieved by immunohistochemistry (IHC) on the protein level using tissue microarrays (TMAs), the method most widely applied when analyzing large sample numbers. Objective: We aimed to investigate ITH by IHC in bladder cancer TMAs. Methods: Staining for eleven immunohistochemical markers (CK5, Cyclin D1, E-Cadherin, EGFR, FGFR, GATA3, HER2, p16, p63, P-Cadherin and RB1)was performed, and differences in staining patterns were assessed both within 1981 individual tissue-cores and by comparing two cores from the same tumor in 948 cases according to our pre-specified criteria. Presence of ITH was associated with clinicopathological data such as stage, grade, molecular subtype and survival. Results: Intracore ITH in one or several markerswas associated with grade 3, stage T1 and the genomically unstable molecular subtype. ITH in three or more markers was found in 5% between cores (intercore heterogeneity) and in 2% within cores (intracore heterogeneity). No association with survival was found for any of the ITH groups. Conclusions: We observed ITH in a small proportion of the tumors, suggesting that ITH has only a limited impact on TMA bladder cancer studies.
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| 7. |
- Marzouka, Nour Al Dain, et al.
(author)
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A validation and extended description of the Lund taxonomy for urothelial carcinoma using the TCGA cohort
- 2018
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In: Scientific Reports. - : Springer Science and Business Media LLC. - 2045-2322. ; 8:1
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Journal article (peer-reviewed)abstract
- Global gene expression analysis has been a major tool for urothelial carcinoma subtype discovery. This approach has revealed extensive complexity both in intrinsic features of the tumor cells and in the microenvironment. However, global gene expression cannot distinguish between gene expression signals originating from the tumor cells proper and from normal cells in the biopsy. Here, we use a large cohort of advanced urothelial carcinomas for which both gene expression data and extensive immunohistochemistry are available to create a supervised mRNA expression centroid classifier. This classifier identifies the major Lund taxonomy tumor cell phenotypes as defined by IHC. We apply this classifier to the independent TCGA dataset and show excellent associations between identified subtypes and genomic features. We validate a progressed version of Urothelial-like A (UroA-Prog) that shows FGFR3 mutations and CDKN2A deletions, and we show that the variant Urothelial-like C is almost devoid of FGFR3 mutations. We show that Genomically Unstable tumors are very distinct from Urothelial-like tumors at the genomic level, and that tumors classified as Basal/SCC-like all complied with the established definition for Basal/SCC-like tumors. We identify the Mesenchymal-like and Small-cell/Neuroendocrine-like subtypes, and demonstrate that patients with UroB and Sc/NE-like tumors show the worst overall survival.
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| 8. |
- Marzouka, Nour-al-dain, et al.
(author)
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CopyNumber450kCancer : baseline correction for accurate copy number calling from the 450k methylation array
- 2016
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In: Bioinformatics. - : Oxford University Press (OUP). - 1367-4803 .- 1367-4811. ; 32:7, s. 1080-1082
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Journal article (peer-reviewed)abstract
- The Illumina Infinium HumanMethylation450 BeadChip (450k) is widely used for the evaluation of DNA methylation levels in large-scale datasets, particularly in cancer. The 450k design allows copy number variant (CNV) calling using existing bioinformatics tools. However, in cancer samples, numerous large-scale aberrations cause shifting in the probe intensities and thereby may result in erroneous CNV calling. Therefore, a baseline correction process is needed. We suggest the maximum peak of probe segment density to correct the shift in the intensities in cancer samples.
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| 9. |
- Marzouka, Nour-Al-Dain, et al.
(author)
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multiclassPairs: An R package to train multiclass pair-based classifier
- 2021
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In: Bioinformatics. - : Oxford University Press (OUP). - 1367-4803 .- 1460-2059. ; 37:18, s. 3043-3044
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Journal article (peer-reviewed)abstract
- Motivationk–Top Scoring Pairs (kTSP) algorithms utilize in-sample gene expression feature pair rules for class prediction, and have demonstrated excellent performance and robustness. The available packages and tools primarily focus on binary prediction (i.e. two classes). However, many real-world classification problems e.g., tumor subtype prediction, are multiclass tasks.ResultsHere, we present multiclassPairs, an R package to train pair-based single sample classifiers for multiclass problems. multiclassPairs offers two main methods to build multiclass prediction models, either using a one-vs-rest kTSP scheme or through a novel pair-based Random Forest approach. The package also provides options for dealing with class imbalances, multiplatform training, missing features in test data, and visualization of training and test results.Availability‘multiclassPairs’ package is available on CRAN servers and GitHub: https://github.com/NourMarzouka/multiclassPairsSupplementary informationSupplementary data are available at Bioinformatics online.
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| 10. |
- Marzouka, Nour Al Dain, et al.
(author)
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Recurring urothelial carcinomas show genomic rearrangements incompatible with a direct relationship
- 2020
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In: Scientific Reports. - : Springer Science and Business Media LLC. - 2045-2322. ; 10:1
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Journal article (peer-reviewed)abstract
- We used the fact that patients with non-muscle invasive bladder tumors show local recurrences and multiple tumors to study re-initiation of tumor growth from the same urothelium. By extensive genomic analyses we show that tumors from the same patient are clonal. We show that gross genomic chromosomal aberrations may be detected in one tumor, only to be undetected in a recurrent tumor. By analyses of incompatible changes i.e., genomic alterations that cannot be reversed, we show that almost all tumors from a single patient may show such changes, thus the tumors cannot have originated from each other. As recurring tumors share both genomic alterations and driver gene mutations, these must have been present in the urothelium in periods with no tumor growth. We present a model that includes a growing and evolving field of urothelial cells that occasionally, and locally, produce bursts of cellular growth leading to overt tumors.
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