| Literature DB >> 35158934 |
Alexandros Karagiannakos1, Maria Adamaki1, Antonis Tsintarakis1, Borek Vojtesek2, Robin Fåhraeus2,3,4,5, Vassilis Zoumpourlis1, Konstantinos Karakostis1,3,6.
Abstract
Cancer is the second leading cause of death globally. One of the main hallmarks in cancer is the functional deregulation of crucial molecular pathways via driver genetic events that lead to abnormal gene expression, giving cells a selective growth advantage. Driver events are defined as mutations, fusions and copy number alterations that are causally implicated in oncogenesis. Molecular analysis on tissues that have originated from a wide range of anatomical areas has shown that mutations in different members of several pathways are implicated in different cancer types. In recent decades, significant efforts have been made to incorporate this knowledge into daily medical practice, providing substantial insight towards clinical diagnosis and personalized therapies. However, since there is still a strong need for more effective drug development, a deep understanding of the involved signaling mechanisms and the interconnections between these pathways is highly anticipated. Here, we perform a systemic analysis on cancer patients included in the Pan-Cancer Atlas project, with the aim to select the ten most highly mutated signaling pathways (p53, RTK-RAS, lipids metabolism, PI-3-Kinase/Akt, ubiquitination, b-catenin/Wnt, Notch, cell cycle, homology directed repair (HDR) and splicing) and to provide a detailed description of each pathway, along with the corresponding therapeutic applications currently being developed or applied. The ultimate scope is to review the current knowledge on highly mutated pathways and to address the attractive perspectives arising from ongoing experimental studies for the clinical implementation of personalized medicine.Entities:
Keywords: NGS; cancer patients; clinical implementation; molecular oncology; mutations; precision medicine; tumor
Year: 2022 PMID: 35158934 PMCID: PMC8833388 DOI: 10.3390/cancers14030664
Source DB: PubMed Journal: Cancers (Basel) ISSN: 2072-6694 Impact factor: 6.639
Figure 1Somatic driver mutational frequency of 204 cancer genes involved in 27 signaling pathways implicated in six major cellular procedures. For the calculations, mutational data from 10,439 tumor samples were examined. Percentages refer to the total number of samples examined (10,439).
Figure 2Crucial signaling pathways implicated in 25 cancer types/subtypes per disease stage. For this analysis, 5283 tumor samples with an available mutational profile and disease stage were examined. Here, only signaling pathways altered in at least 20 of the examined samples for each cancer type/subtype are shown. N: number of samples examined; n: number of samples that harbor somatic driver mutations in each signaling pathway; pdm: proportion of samples of a particular cancer type/subtype that harbor at least one somatic driver mutation in genes of a particular signaling pathway.
Figure 3Alteration rate of 27 signaling pathways across 36 cancer types/subtypes. For this analysis, 10,066 tumor samples of primary origin and with available mutational profiles were examined for the presence of somatic driver mutations in our 204 genes of interest. Calculations were performed by taking into account all the available mutationally profiled primary tumor samples of the cBioPortal selected studies (10,066 samples) instead of the driver event-harboring mutationally profiled primary tumor samples (7915 samples). If for a selected cancer type there were x mutationally profiled primary tumor samples available in the cBioPortal selected studies, then, y samples would bear at least one driver event in at least one of the 204 genes of interest and z samples would harbor driver events in genes participating in a selected signaling pathway. The corresponding driver mutational rate for this cancer type-signaling pathway pair is calculated as (z/x) × 100. Here, only cancer types/subtypes that entail more than 50 analyzed samples are shown. From left to right, signaling pathways are displayed in descending order of total mutational frequency. n: number of samples examined.
FDA approved drugs targeting the signaling of 18 cancer-related genes of the RTK-RAS pathway. Drugs that specifically target only the corresponding gene are shown in blue color. Drugs granted with a Breakthrough Therapy Designation but not yet approved by the FDA, are not included in this table.
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| Bosutinib, Brigatinib, Dasatinib, Ibrutinib, Imatinib, Niotinib, Pazopanib, Ponatinib, Regorafenib, Sunitinib, Tivozanib, Vandetanib |
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| Alectinib, Brigatinib, Ceritinib, Crizotinib, Entrectinib, Gilteritinib, Lorlatinib, Sunitinib |
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| Binimetinib, Cobimetinib, Dabrafenib, Dasatinib, Encorafenib, Regorafenib, Sorafenib, Trametinib, |
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| Afatinib, Brigatinib, Ceritinib, |
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| Afatinib, Dacomitinib, Everolimus, Gefitinib, Ibrutinib, Lapatinib, |
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| Brigatinib, Dasatinib, Erdafitinib, Infigratinib, Lenvatinib, Nintedanib, Pazopanib, Ponatinib, Regorafenib, Sorafenib, Sunitinib, Tivozanib, Vandetanib |
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| Brigatinib, Ceritinib, Erdafitinib, Infigratinib, Lenvatinib, Nintedanib, Pazopanib, Regorafenib, Sorafenib, Sunitinib, Vandetanib |
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| Brigatinib, Cabozatinib, Ceritinib, Fedratinib, Gilteritinib, Ibrutinib, Midostaurin, Nintedanib, Pexidartinib, Sorafenib, Sunitinib, Vandetanib |
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| Axitinib, Cabozatinib, Dasatinib, Fedratinib, Imatinib, Infigratinib, Lenvatinib, Midostaurin, Nilotinib, Pazopanib, Pexidartinib, Ponatinib, Regorafenib, Sorafenib, Sunitinib, Tivozanib |
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| Binimetinib, Cobimetinib, |
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| Cabozatinib, |
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| Binimetinib, Cobimetinib, Trametinib |
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| Cabozatinib, Crizotinib, Entrectinib, Larotrectinib, Lorlatinib, Regorafenib, Sorafenib, Sunitinib |
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| Cabozatinib, Entrectinib, Larotrectinib, Lorlatinib, Sorafenib, Sunitinib |
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| Axitinib, Dasatinib, Ibrutinib, Imatinib, Lenvatinib, Midostaurin, Nilotinib, Nintedanib, |
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| Binimetinib, Cobimetinib, Trametinib |
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| Alectinib, Brigatinib, Cabozatinib, Ceritinib, Fedratinib, Ibrutinib, Lenvatinib, Pazopanib, Ponatinib, Pralsetinib, Regorafenib, |
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| Brigatinib, Cabozatinib, Ceritinib, Crizotinib, Entrectinib, Lorlatinib |
FDA approved drugs targeting the signaling of four cancer-related genes of the lipid metabolism pathway. Drugs that specifically target only the corresponding gene are shown in blue color.
| Gene Signaling | Drugs |
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| Alpelisib, Copanlisib, Duvelisib, Everolimus, Idelalisib, Midostaurin, Sirolimus, Temsirolimus, Umbralisib |
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| Alpelisib, Copanlisib, Duvelisib, Everolimus, Metformin, Midostaurin, Sirolimus, Temsirolimus |