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  • 1
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    Online Resource
    Body composition and lung cancer-associated cachexia in TRACERx
    Springer Science and Business Media LLC ; 2023
    In:  Nature Medicine Vol. 29, No. 4 ( 2023-04), p. 846-858
    Details
    In: Nature Medicine, Springer Science and Business Media LLC, Vol. 29, No. 4 ( 2023-04), p. 846-858
    Type of Medium: Online Resource
    ISSN: 1078-8956 , 1546-170X
    URL: Article
    DOI: 10.1038/s41591-023-02232-8
    Language: English
    Publisher: Springer Science and Business Media LLC
    Publication Date: 2023
    detail.hit.zdb_id: 1484517-9
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  • 2
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    Computational Analysis Reveals the Temporal Acquisition of Pathway Alterations during the Evolution of Cancer
    MDPI AG ; 2022
    In:  Cancers Vol. 14, No. 23 ( 2022-11-25), p. 5817-
    Details
    In: Cancers, MDPI AG, Vol. 14, No. 23 ( 2022-11-25), p. 5817-
    Abstract: Cancer metastasis is the lethal developmental step in cancer, responsible for the majority of cancer deaths. To metastasise, cancer cells must acquire the ability to disseminate systemically and to escape an activated immune response. Here, we endeavoured to investigate if metastatic dissemination reflects acquisition of genomic traits that are selected for. We acquired mutation and copy number data from 8332 tumours representing 19 cancer types acquired from The Cancer Genome Atlas and the Hartwig Medical Foundation. A total of 827,344 non-synonymous mutations across 8332 tumour samples representing 19 cancer types were timed as early or late relative to copy number alterations, and potential driver events were annotated. We found that metastatic cancers had a significantly higher proportion of clonal mutations and a general enrichment of early mutations in p53 and RTK/KRAS pathways. However, while individual pathways demonstrated a clear time-separated preference for specific events, the relative timing did not vary between primary and metastatic cancers. These results indicate that the selective pressure that drives cancer development does not change dramatically between primary and metastatic cancer on a genomic level, and is mainly focused on alterations that increase proliferation.
    Type of Medium: Online Resource
    ISSN: 2072-6694
    URL: Article
    DOI: 10.3390/cancers14235817
    Language: English
    Publisher: MDPI AG
    Publication Date: 2022
    detail.hit.zdb_id: 2527080-1
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  • 3
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    The ratio of adaptive to innate immune cells differs between genders and associates with improved prognosis and response to immunotherapy
    Public Library of Science (PLoS) ; 2023
    In:  PLOS ONE Vol. 18, No. 2 ( 2023-2-6), p. e0281375-
    Details
    In: PLOS ONE, Public Library of Science (PLoS), Vol. 18, No. 2 ( 2023-2-6), p. e0281375-
    Abstract: Immunotherapy has revolutionised cancer treatment. However, not all cancer patients benefit, and current stratification strategies based primarily on PD1 status and mutation burden are far from perfect. We hypothesised that high activation of an innate response relative to the adaptive response may prevent proper tumour neoantigen identification and decrease the specific anticancer response, both in the presence and absence of immunotherapy. To investigate this, we obtained transcriptomic data from three large publicly available cancer datasets, the Cancer Genome Atlas (TCGA), the Hartwig Medical Foundation (HMF), and a recently published cohort of metastatic bladder cancer patients treated with immunotherapy. To analyse immune infiltration into bulk tumours, we developed an RNAseq-based model based on previously published definitions to estimate the overall level of infiltrating innate and adaptive immune cells from bulk tumour RNAseq data. From these, the adaptive-to-innate immune ratio (A/I ratio) was defined. A meta-analysis of 32 cancer types from TCGA overall showed improved overall survival in patients with an A/I ratio above median (Hazard ratio (HR) females 0.73, HR males 0.86, P 〈 0.05). Of particular interest, we found that the association was different for males and females for eight cancer types, demonstrating a gender bias in the relative balance of the infiltration of innate and adaptive immune cells. For patients with metastatic disease, we found that responders to immunotherapy had a significantly higher A/I ratio than non-responders in HMF (P = 0.036) and a significantly higher ratio in complete responders in a separate metastatic bladder cancer dataset (P = 0.022). Overall, the adaptive-to-innate immune ratio seems to define separate states of immune activation, likely linked to fundamental immunological reactions to cancer. This ratio was associated with improved prognosis and improved response to immunotherapy, demonstrating potential relevance to patient stratification. Furthermore, by demonstrating a significant difference between males and females that associates with response, we highlight an important gender bias which likely has direct clinical relevance.
    Type of Medium: Online Resource
    ISSN: 1932-6203
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    DOI: 10.1371/journal.pone.0281375
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    Language: English
    Publisher: Public Library of Science (PLoS)
    Publication Date: 2023
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  • 4
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    27 Cytokine signature of PD-1, CXCL10, and TNF-alpha predicts response to nivolumab and ipilimumab
    BMJ ; 2021
    In:  Journal for ImmunoTherapy of Cancer Vol. 9, No. Suppl 2 ( 2021-11), p. A32-A32
    Details
    In: Journal for ImmunoTherapy of Cancer, BMJ, Vol. 9, No. Suppl 2 ( 2021-11), p. A32-A32
    Abstract: Checkpoint inhibitors have significantly improved treatment of metastatic melanoma. Yet, 40–60% of the patients do not achieve a long-term benefit from such immunotherapy. Thus, there is an urgent need to identify biomarkers that can predict response to immunotherapy to guide patients for the best possible treatment. Here, we evaluate an unsupervised machine learning approach to identify potential cytokine signatures from liquid biopsies that predict response to immunotherapy in melanoma. Methods Blood samples were drawn from 74 patients diagnosed with unresectable advanced-stage melanoma undergoing treatment with first-line nivolumab/ipilimumab or pembrolizumab between August 2017 – July 2019 at Aarhus University Hospital, Denmark. Blood samples were tested for plasma levels of PD-1, PD-L1, IFN-beta, IFN-gamma, CCL20, CXCL5, CXCL10, IL6, IL8, IL10, MCP1, and TNF-alpha by Meso Scale ELISA assays. Healthy controls were used to compare general cytokine levels in plasma. A bioinformatic workflow consisting of Uniform Manifold Approximation and Projection (UMAP) dimension reduction method and k-means clustering analysis was applied to define clusters based on the cytokine profile, followed by survival analysis of the clusters. Results UMAP analysis demonstrated that the cytokine profile at baseline was similar for healthy controls and patients, regardless of treatment. Upon treatment initiation, the cytokine profile changed in a treatment-dependent way to be significantly different between patient groups. Clustering defined by the cytokine profile measured early during treatment in nivolumab/ipilimumab treated patients identified two clusters associated with superior progression-free survival (PFS) (log-rank p=0.018). We identified that these cluster were characterized by significantly higher levels of PD-1, CXCL10, and TNF-alpha. UMAP analysis of the cytokine level as fold change over baseline level, confirmed that nivolumab/ipilimumab patients with superior PFS were characterized by higher levels of PD-1, CXCL10, and TNF-alpha. Cox regression analysis revealed high fold change of PD-1 as a strong predictor for superior PFS (HR=0.29; 95% CI 0.12–0.66; p=0.0032). However, a similar cytokine profile was not associated to superior PFS in patients receiving pembrolizumab, suggesting that the cytokine signature is specific for nivolumab/ipilimumab treatment. Conclusions Using unsupervised machine learning we identified a cytokine signature of high PD-1, CXCL10, and TNF-alpha to be associated with superior PFS in advanced-stage melanoma patients treated with nivolumab/ipilimumab but not pembrolizumab, with high fold change of PD-1 being a strong individual predictor for PFS. Acknowledgements We thank the medical laboratory technicians who collected blood samples and the patients who participated in the study. Ethics Approval The study was approved by Central Denmark Region Committees on Biomedical Research Ethics, approval number 1-10-72-374-15.
    Type of Medium: Online Resource
    ISSN: 2051-1426
    URL: Article
    DOI: 10.1136/jitc-2021-SITC2021.027
    Language: English
    Publisher: BMJ
    Publication Date: 2021
    detail.hit.zdb_id: 2719863-7
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  • 5
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    Lung adenocarcinoma promotion by air pollutants
    Springer Science and Business Media LLC ; 2023
    In:  Nature Vol. 616, No. 7955 ( 2023-04-06), p. 159-167
    Details
    In: Nature, Springer Science and Business Media LLC, Vol. 616, No. 7955 ( 2023-04-06), p. 159-167
    Type of Medium: Online Resource
    ISSN: 0028-0836 , 1476-4687
    URL: Article
    DOI: 10.1038/s41586-023-05874-3
    RVK:
    TA 1000
    RVK:
    UA 1000
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    WA 15000
    Language: English
    Publisher: Springer Science and Business Media LLC
    Publication Date: 2023
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    detail.hit.zdb_id: 1413423-8
    SSG: 11
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  • 6
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    Abstract 624: Classifying cGAS-STING activity links chromosomal instability with immunotherapy response in metastatic bladder cancer
    American Association for Cancer Research (AACR) ; 2022
    In:  Cancer Research Vol. 82, No. 12_Supplement ( 2022-06-15), p. 624-624
    Details
    In: Cancer Research, American Association for Cancer Research (AACR), Vol. 82, No. 12_Supplement ( 2022-06-15), p. 624-624
    Abstract: The cGAS-STING pathway serves a critical role in anti-cancer therapy. Particularly, response to immunotherapy is likely driven by both active cGAS-STING signaling that attracts immune cells, and by the presence of cancer neoantigens that presents as targets for cytotoxic T-cells. Chromosomal instability (CIN) is a hallmark of cancer, but also leads to an accumulation of cytosolic DNA that in turn results in increased cGAS-STING signaling. To avoid triggering the cGAS-STING pathway, it is commonly disrupted by the cancer cells, either through mutations in the pathway or through transcriptional silencing. Given its effect on the immune system, determining the cGAS-STING activation status prior to treatment initiation is likely of clinical relevance, but to date no robust method has been developed. Here, we used combined expression data from 2307 tumors from five cancer types from The Cancer Genome Atlas (TCGA) to define a novel cGAS-STING activity score based on eight genes with a known role in the pathway. Using unsupervised clustering, four distinct categories of cGAS-STING activation were identified. In multivariate models, the cGAS-STING active tumors show improved prognosis. Importantly, in an independent bladder cancer immunotherapy treated cohort, patients without cGAS-STING activation showed very limited response to treatment, while patients with strong cGAS-STING activation showed improved response and improved prognosis, particularly among patients with high CIN and high numbers of neoantigens. In a multivariate model, a significant interaction was observed between CIN, neoantigens, and cGAS-STING activation. Together, this supports a role of cGAS-STING activity as a predictive biomarker in combination with measures of CIN and neoantigens for the application of immunotherapy. Citation Format: Mateo Sokac. Classifying cGAS-STING activity links chromosomal instability with immunotherapy response in metastatic bladder cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 624.
    Type of Medium: Online Resource
    ISSN: 1538-7445
    URL: Article
    DOI: 10.1158/1538-7445.AM2022-624
    Language: English
    Publisher: American Association for Cancer Research (AACR)
    Publication Date: 2022
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  • 7
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    A local human Vδ1 T cell population is associated with survival in nonsmall-cell lung cancer
    Springer Science and Business Media LLC ; 2022
    In:  Nature Cancer Vol. 3, No. 6 ( 2022-05-30), p. 696-709
    Details
    In: Nature Cancer, Springer Science and Business Media LLC, Vol. 3, No. 6 ( 2022-05-30), p. 696-709
    Abstract: Murine tissues harbor signature γδ T cell compartments with profound yet differential impacts on carcinogenesis. Conversely, human tissue-resident γδ cells are less well defined. In the present study, we show that human lung tissues harbor a resident Vδ1 γδ T cell population. Moreover, we demonstrate that Vδ1 T cells with resident memory and effector memory phenotypes were enriched in lung tumors compared with nontumor lung tissues. Intratumoral Vδ1 T cells possessed stem-like features and were skewed toward cytolysis and helper T cell type 1 function, akin to intratumoral natural killer and CD8 + T cells considered beneficial to the patient. Indeed, ongoing remission post-surgery was significantly associated with the numbers of CD45RA − CD27 − effector memory Vδ1 T cells in tumors and, most strikingly, with the numbers of CD103 + tissue-resident Vδ1 T cells in nonmalignant lung tissues. Our findings offer basic insights into human body surface immunology that collectively support integrating Vδ1 T cell biology into immunotherapeutic strategies for nonsmall cell lung cancer.
    Type of Medium: Online Resource
    ISSN: 2662-1347
    URL: Article
    DOI: 10.1038/s43018-022-00376-z
    Language: English
    Publisher: Springer Science and Business Media LLC
    Publication Date: 2022
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  • 8
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    An integrated multi-omics analysis identifies prognostic molecular subtypes of non-muscle-invasive bladder cancer
    Springer Science and Business Media LLC ; 2021
    In:  Nature Communications Vol. 12, No. 1 ( 2021-04-16)
    Details
    In: Nature Communications, Springer Science and Business Media LLC, Vol. 12, No. 1 ( 2021-04-16)
    Abstract: The molecular landscape in non-muscle-invasive bladder cancer (NMIBC) is characterized by large biological heterogeneity with variable clinical outcomes. Here, we perform an integrative multi-omics analysis of patients diagnosed with NMIBC ( n  = 834). Transcriptomic analysis identifies four classes (1, 2a, 2b and 3) reflecting tumor biology and disease aggressiveness. Both transcriptome-based subtyping and the level of chromosomal instability provide independent prognostic value beyond established prognostic clinicopathological parameters. High chromosomal instability, p53-pathway disruption and APOBEC-related mutations are significantly associated with transcriptomic class 2a and poor outcome. RNA-derived immune cell infiltration is associated with chromosomally unstable tumors and enriched in class 2b. Spatial proteomics analysis confirms the higher infiltration of class 2b tumors and demonstrates an association between higher immune cell infiltration and lower recurrence rates. Finally, the independent prognostic value of the transcriptomic classes is documented in 1228 validation samples using a single sample classification tool. The classifier provides a framework for biomarker discovery and for optimizing treatment and surveillance in next-generation clinical trials.
    Type of Medium: Online Resource
    ISSN: 2041-1723
    URL: Article
    DOI: 10.1038/s41467-021-22465-w
    Language: English
    Publisher: Springer Science and Business Media LLC
    Publication Date: 2021
    detail.hit.zdb_id: 2553671-0
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  • 9
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    Abstract 2186: Distinct aggressive biology drives the evolution of metastatic cancer
    American Association for Cancer Research (AACR) ; 2022
    In:  Cancer Research Vol. 82, No. 12_Supplement ( 2022-06-15), p. 2186-2186
    Details
    In: Cancer Research, American Association for Cancer Research (AACR), Vol. 82, No. 12_Supplement ( 2022-06-15), p. 2186-2186
    Abstract: Metastatic disease is responsible for 90% of all cancer deaths. Understanding the process of how primary tumors achieve metastatic potential is of great importance and paramount to the development of precision medicine that may limit the aggressive distant spread of metastatic cancer. It is hypothesized that during cancer evolution, cells within the primary tumor obtain metastatic potential through acquisition of specific somatic alterations. However, the defining ability that allows metastasis remains unknown. By comparing genomic profiles of primary and metastatic cancers we wish to investigate if potential metastatic gate-keeper mutations exist, defined as alterations to individual genes or pathways that are required to facilitate metastatic dissemination.Here, we analyzed panel-based DNA sequencing datasets from the GENIE (Genomics Evidence Neoplasia Information Exchange) project, version 9.0. Analyses were performed on 174 shared cancer genes selected to include as many patients as possible while analyzing as many genes as possible. In total 39,036 patients had mutations or copy number alterations in one or more of the 174 shared genes across 25 different cancer types. Using bioinformatic tools, we compared genomic alterations in primary versus metastatic samples. Metastatic samples harbor a higher tumor mutation burden and increased levels of chromosomal instability. However, while we found a higher total level of driver mutations in metastatic samples, these appear primarily driven by a higher mutation burden, and corrected for this, we found a significantly lower level of drivers compared to primary. Overall, phylogenetic analysis showed that primary and metastatic samples clustered together by cancer type. Comparing two logistic regressions models, which was corrected for tumor mutation burden and genomic instability, we found that despite most genes show a relatively low difference in frequency between primary and metastatic disease, 55 of the 174 genes in this panel showed a small but significant overrepresentation in at least one cancer type in either primary or metastatic disease.With this analysis we demonstrate how the power of large datasets can be utilized to make novel inferences on cancer biology. We observed significant enrichment in overall mutation counts and copy number alterations in metastatic samples. However, we found limited genomic differences between primary and metastatic cancer within the same cancer types. This might suggest that acquisition of cancer driver mutations are initially mostly shaped by the tissue of origin where specific cancer driver mutations define the developing primary tumor, while acquisition of driver mutations that contribute to metastatic disease are less specific. It might indicate that the metastatic process is driven less by newly acquired metastatic features, but more by non-cancer features such as inflammation in the surrounding tissue. Citation Format: Ditte Sigaard Christensen, Johanne Ahrenfeldt, Mateo Sokač, Judit Kisistók, Nicholas McGranahan, Nicolai Juul Birkbak. Distinct aggressive biology drives the evolution of metastatic cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 2186.
    Type of Medium: Online Resource
    ISSN: 1538-7445
    URL: Article
    DOI: 10.1158/1538-7445.AM2022-2186
    Language: English
    Publisher: American Association for Cancer Research (AACR)
    Publication Date: 2022
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  • 10
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    Spatial transformation of multi-omics data unlocks novel insights into cancer biology
    eLife Sciences Publications, Ltd ; 2023
    In:  eLife Vol. 12 ( 2023-09-05)
    Details
    In: eLife, eLife Sciences Publications, Ltd, Vol. 12 ( 2023-09-05)
    Abstract: The application of next-generation sequencing (NGS) has transformed cancer research. As costs have decreased, NGS has increasingly been applied to generate multiple layers of molecular data from the same samples, covering genomics, transcriptomics, and methylomics. Integrating these types of multi-omics data in a combined analysis is now becoming a common issue with no obvious solution, often handled on an ad hoc basis, with multi-omics data arriving in a tabular format and analyzed using computationally intensive statistical methods. These methods particularly ignore the spatial orientation of the genome and often apply stringent p-value corrections that likely result in the loss of true positive associations. Here, we present GENIUS (GEnome traNsformatIon and spatial representation of mUltiomicS data), a framework for integrating multi-omics data using deep learning models developed for advanced image analysis. The GENIUS framework is able to transform multi-omics data into images with genes displayed as spatially connected pixels and successfully extract relevant information with respect to the desired output. We demonstrate the utility of GENIUS by applying the framework to multi-omics datasets from the Cancer Genome Atlas. Our results are focused on predicting the development of metastatic cancer from primary tumors, and demonstrate how through model inference, we are able to extract the genes which are driving the model prediction and are likely associated with metastatic disease progression. We anticipate our framework to be a starting point and strong proof of concept for multi-omics data transformation and analysis without the need for statistical correction.
    Type of Medium: Online Resource
    ISSN: 2050-084X
    URL: Article
    DOI: 10.7554/eLife.87133
    Language: English
    Publisher: eLife Sciences Publications, Ltd
    Publication Date: 2023
    detail.hit.zdb_id: 2687154-3
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