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      Similar genetic profile in early and late stage urothelial tract cancer

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          Abstract

          Introduction

          Urothelial tract cancer (UTC) ranks as the tenth most prevalent cancer and holds the seventh position in terms of mortality worldwide. Despite its prevalence and mortality ranking, there are still gaps in the knowledge of the mutational landscape in patients with advanced disease who have limited therapeutic options after multiple lines of prior treatment. This study compares the genomic and transcriptomic landscape, and targeted treatment options between metastatic UTC (mUTC) patients treated with multiple lines of therapy compared to newly diagnosed, untreated Muscle Invasive Bladder Cancer (MIBC).

          Methods

          We compared genomic and clinical data from two cohorts: mUTC patients who received multiple lines of therapy and were referred to the Copenhagen Prospective Personalized Oncology (CoPPO) project at Rigshospitalet, University of Copenhagen. Data for MIBC UTC patients were acquired from the Cancer Genome Atlas Bladder Cancer (TCGA BLCA) cohort. Biopsies in CoPPO were performed at the time of enrollment. 523 highly important cancer-related genes (TrueSight Oncology-500 targeted sequencing panel) were used from both cohorts for comparative analysis. Analyses included RNA count data to compare predicted molecular subtypes in each cohort separately.

          Results

          Patients from the CoPPO cohort had a lower median age at first-line treatment than the TCGA BLCA cohort, with no significant gender disparity. The predominant histology was urothelial cell carcinoma in both cohorts. Genomic analysis revealed no significant difference between the top mutated genes in the two cohorts, specifically looking into DNA damage repair genes. Molecular subtyping indicated a higher frequency of neuroendocrine differentiation in the CoPPO cohort. 13% of patients in the CoPPO cohort received targeted therapy based on genomic findings, and 16% received non-targeted treatment, totaling 29% receiving CoPPO treatment (9 patients). The remaining 71% received best supportive care. Kaplan-Meier analysis showed a non-significant survival benefit for the intervention group in the CoPPO cohort.

          Conclusion

          When focusing on 523 highly relevant cancer genes, the mutational profile of mUTC patients who have undergone numerous treatment lines resembles that of newly diagnosed MIBC. These alterations can be targeted, indicating the potential advantage of early genomic testing for personalized treatment within clinical trials.

          Supplementary Information

          The online version contains supplementary material available at 10.1007/s00432-024-05850-y.

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          Most cited references50

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          Global cancer statistics 2020: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries

          This article provides an update on the global cancer burden using the GLOBOCAN 2020 estimates of cancer incidence and mortality produced by the International Agency for Research on Cancer. Worldwide, an estimated 19.3 million new cancer cases (18.1 million excluding nonmelanoma skin cancer) and almost 10.0 million cancer deaths (9.9 million excluding nonmelanoma skin cancer) occurred in 2020. Female breast cancer has surpassed lung cancer as the most commonly diagnosed cancer, with an estimated 2.3 million new cases (11.7%), followed by lung (11.4%), colorectal (10.0 %), prostate (7.3%), and stomach (5.6%) cancers. Lung cancer remained the leading cause of cancer death, with an estimated 1.8 million deaths (18%), followed by colorectal (9.4%), liver (8.3%), stomach (7.7%), and female breast (6.9%) cancers. Overall incidence was from 2-fold to 3-fold higher in transitioned versus transitioning countries for both sexes, whereas mortality varied <2-fold for men and little for women. Death rates for female breast and cervical cancers, however, were considerably higher in transitioning versus transitioned countries (15.0 vs 12.8 per 100,000 and 12.4 vs 5.2 per 100,000, respectively). The global cancer burden is expected to be 28.4 million cases in 2040, a 47% rise from 2020, with a larger increase in transitioning (64% to 95%) versus transitioned (32% to 56%) countries due to demographic changes, although this may be further exacerbated by increasing risk factors associated with globalization and a growing economy. Efforts to build a sustainable infrastructure for the dissemination of cancer prevention measures and provision of cancer care in transitioning countries is critical for global cancer control.
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            Maftools: efficient and comprehensive analysis of somatic variants in cancer

            Numerous large-scale genomic studies of matched tumor-normal samples have established the somatic landscapes of most cancer types. However, the downstream analysis of data from somatic mutations entails a number of computational and statistical approaches, requiring usage of independent software and numerous tools. Here, we describe an R Bioconductor package, Maftools, which offers a multitude of analysis and visualization modules that are commonly used in cancer genomic studies, including driver gene identification, pathway, signature, enrichment, and association analyses. Maftools only requires somatic variants in Mutation Annotation Format (MAF) and is independent of larger alignment files. With the implementation of well-established statistical and computational methods, Maftools facilitates data-driven research and comparative analysis to discover novel results from publicly available data sets. In the present study, using three of the well-annotated cohorts from The Cancer Genome Atlas (TCGA), we describe the application of Maftools to reproduce known results. More importantly, we show that Maftools can also be used to uncover novel findings through integrative analysis.
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              OncoKB: A Precision Oncology Knowledge Base

              Purpose With prospective clinical sequencing of tumors emerging as a mainstay in cancer care, an urgent need exists for a clinical support tool that distills the clinical implications associated with specific mutation events into a standardized and easily interpretable format. To this end, we developed OncoKB, an expert-guided precision oncology knowledge base. Methods OncoKB annotates the biologic and oncogenic effects and prognostic and predictive significance of somatic molecular alterations. Potential treatment implications are stratified by the level of evidence that a specific molecular alteration is predictive of drug response on the basis of US Food and Drug Administration labeling, National Comprehensive Cancer Network guidelines, disease-focused expert group recommendations, and scientific literature. Results To date, > 3,000 unique mutations, fusions, and copy number alterations in 418 cancer-associated genes have been annotated. To test the utility of OncoKB, we annotated all genomic events in 5,983 primary tumor samples in 19 cancer types. Forty-one percent of samples harbored at least one potentially actionable alteration, of which 7.5% were predictive of clinical benefit from a standard treatment. OncoKB annotations are available through a public Web resource ( http://oncokb.org ) and are incorporated into the cBioPortal for Cancer Genomics to facilitate the interpretation of genomic alterations by physicians and researchers. Conclusion OncoKB, a comprehensive and curated precision oncology knowledge base, offers oncologists detailed, evidence-based information about individual somatic mutations and structural alterations present in patient tumors with the goal of supporting optimal treatment decisions.
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                Author and article information

                Contributors
                dag.rune.stormoen@regionh.dk
                Journal
                J Cancer Res Clin Oncol
                J Cancer Res Clin Oncol
                Journal of Cancer Research and Clinical Oncology
                Springer Berlin Heidelberg (Berlin/Heidelberg )
                0171-5216
                1432-1335
                8 July 2024
                8 July 2024
                2024
                : 150
                : 7
                : 339
                Affiliations
                [1 ]GRID grid.475435.4, Department of Oncology, , Copenhagen University Hospital Rigshospitalet, ; Blegdamsvej 9, Copenhagen, 5073 Denmark
                [2 ]Department of Clinical Medicine, University of Copenhagen, ( https://ror.org/035b05819) Copenhagen, Denmark
                [3 ]Department of Radiation Oncology, Dana Farber Cancer Institute, ( https://ror.org/02jzgtq86) Boston, MA USA
                [4 ]GRID grid.38142.3c, ISNI 000000041936754X, Harvard Medical School, ; Boston, MA USA
                [5 ]Computational Health Informatics Program, Boston Children’s Hospital, ( https://ror.org/00dvg7y05) Boston, MA USA
                [6 ]Translational Cancer Genomics Group, Danish Cancer Society, ( https://ror.org/03ytt7k16) Copenhagen, Denmark
                [7 ]GRID grid.475435.4, Department for Genomic Medicine, , Copenhagen University Hospital Rigshospitalet, ; Copenhagen, Denmark
                Article
                5850
                10.1007/s00432-024-05850-y
                11230994
                38976041
                0bb9b3d8-f95f-4c7e-ad51-dff3194ace6f
                © The Author(s) 2024

                Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.

                History
                : 13 May 2024
                : 14 June 2024
                Funding
                Funded by: Copenhagen University
                Categories
                Research
                Custom metadata
                © Springer-Verlag GmbH Germany, part of Springer Nature 2024

                Oncology & Radiotherapy
                urothelial tract cancer,genomic evolution,targeted therapy,molecular subtyping,phase 1 trials

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