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- Campbell, PJ, et al.
(författare)
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Pan-cancer analysis of whole genomes
- 2020
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Ingår i: Nature. - : Springer Science and Business Media LLC. - 1476-4687 .- 0028-0836. ; 578:7793, s. 82-
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Tidskriftsartikel (refereegranskat)abstract
- Cancer is driven by genetic change, and the advent of massively parallel sequencing has enabled systematic documentation of this variation at the whole-genome scale1–3. Here we report the integrative analysis of 2,658 whole-cancer genomes and their matching normal tissues across 38 tumour types from the Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium of the International Cancer Genome Consortium (ICGC) and The Cancer Genome Atlas (TCGA). We describe the generation of the PCAWG resource, facilitated by international data sharing using compute clouds. On average, cancer genomes contained 4–5 driver mutations when combining coding and non-coding genomic elements; however, in around 5% of cases no drivers were identified, suggesting that cancer driver discovery is not yet complete. Chromothripsis, in which many clustered structural variants arise in a single catastrophic event, is frequently an early event in tumour evolution; in acral melanoma, for example, these events precede most somatic point mutations and affect several cancer-associated genes simultaneously. Cancers with abnormal telomere maintenance often originate from tissues with low replicative activity and show several mechanisms of preventing telomere attrition to critical levels. Common and rare germline variants affect patterns of somatic mutation, including point mutations, structural variants and somatic retrotransposition. A collection of papers from the PCAWG Consortium describes non-coding mutations that drive cancer beyond those in the TERT promoter4; identifies new signatures of mutational processes that cause base substitutions, small insertions and deletions and structural variation5,6; analyses timings and patterns of tumour evolution7; describes the diverse transcriptional consequences of somatic mutation on splicing, expression levels, fusion genes and promoter activity8,9; and evaluates a range of more-specialized features of cancer genomes8,10–18.
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- Menden, MP, et al.
(författare)
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Community assessment to advance computational prediction of cancer drug combinations in a pharmacogenomic screen
- 2019
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Ingår i: Nature communications. - : Springer Science and Business Media LLC. - 2041-1723. ; 10:1, s. 2674-
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Tidskriftsartikel (refereegranskat)abstract
- The effectiveness of most cancer targeted therapies is short-lived. Tumors often develop resistance that might be overcome with drug combinations. However, the number of possible combinations is vast, necessitating data-driven approaches to find optimal patient-specific treatments. Here we report AstraZeneca’s large drug combination dataset, consisting of 11,576 experiments from 910 combinations across 85 molecularly characterized cancer cell lines, and results of a DREAM Challenge to evaluate computational strategies for predicting synergistic drug pairs and biomarkers. 160 teams participated to provide a comprehensive methodological development and benchmarking. Winning methods incorporate prior knowledge of drug-target interactions. Synergy is predicted with an accuracy matching biological replicates for >60% of combinations. However, 20% of drug combinations are poorly predicted by all methods. Genomic rationale for synergy predictions are identified, including ADAM17 inhibitor antagonism when combined with PIK3CB/D inhibition contrasting to synergy when combined with other PI3K-pathway inhibitors in PIK3CA mutant cells.
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- Kanai, M, et al.
(författare)
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- 2023
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swepub:Mat__t
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- Chang, PH, et al.
(författare)
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The Prognostic Roles of Pretreatment Circulating Tumor Cells, Circulating Cancer Stem-Like Cells, and Programmed Cell Death-1 Expression on Peripheral Lymphocytes in Patients with Initially Unresectable, Recurrent or Metastatic Head and Neck Cancer: An Exploratory Study of Three Biomarkers in One-time Blood Drawing
- 2019
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Ingår i: Cancers. - : MDPI AG. - 2072-6694. ; 11:4
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Tidskriftsartikel (refereegranskat)abstract
- Circulating tumor cells (CTCs) and immune status are strongly related to cancer prognosis, although few studies have examined both factors. This prospective observational study (ClinicalTrials.gov: NCT02420600) evaluated whether CTCs, circulating cancer stem-like cells (cCSCs), and peripheral lymphocytes with/without Programmed cell death protein 1 (PD-1) expression were associated with prognosis among patients receiving palliative chemotherapy for initially unresectable, recurrent/metastatic head and neck squamous cell carcinoma (rmHNSCC). Thirty-four patients were enrolled between January 2015 and June 2016. Overall survival (OS) was associated with a higher CTC number (hazard ratio [HR]: 1.01, p = 0.0004) and cCSC ratio (HR: 29.903, p < 0.0001). Progression-free survival (PFS) was also associated with CTC number (HR: 1.013, p = 0.002) and cCSC ratio (HR: 10.92, p = 0.003). A CD8+ proportion of ≥ 17% was associated with improved OS (HR: 0.242, p = 0.004). A CD4: CD8 ratio of >1.2 was associated with poorer trend of PFS (HR: 2.12, p = 0.064). PD-1 expression was not associated with survival outcomes. Baseline CTCs, cCSC ratio, and CD8+ ratio may predict prognosis in rmHNSCC.
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- Chen, Y, et al.
(författare)
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Follicular Helper T-Cell-Based Classification of Endometrial Cancer Promotes Precise Checkpoint Immunotherapy and Provides Prognostic Stratification
- 2022
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Ingår i: Frontiers in immunology. - : Frontiers Media SA. - 1664-3224. ; 12, s. 788959-
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Tidskriftsartikel (refereegranskat)abstract
- Despite the fact that management of EC is moving towards four TCGA-based molecular classifications, a pronounced variation in immune response among these molecular subtypes limits its clinical use. We aimed to investigate the determinant biomarker of ICI response in endometrial cancer (EC). We characterized transcriptome signatures associated with tumor immune microenvironment in EC. Two immune infiltration signatures were identified from the TCGA database (n = 520). The high- and low-infiltration clusters were compared for differences in patient clinical characteristics, genomic features, and immune cell transcription signatures for ICI prediction. A Lasso Cox regression model was applied to construct a prognostic gene signature. Time-dependent receiver operating characteristic curve, Kaplan–Meier curve, nomogram, and decision curve analyses were used to assess the prediction capacity. The efficacy of potential biomarker was validated by the Karolinska endometrial cancer cohort (n = 260). Immune signature profiling suggested that T follicular helper–like cells (Tfh) may be an important and favorable factor for EC; high Tfh infiltration showed potential for clinical use in the anti-PD-1 treatment. A Tfh Infiltration Risk Model (TIRM) established using eight genes was validated, and it outperformed the Immune Infiltration Risk Model. The TIRM had a stable prognostic value in combination with clinical risk factors and could be considered as a valuable tool in a clinical prediction model. We identified CRABP1 as an individual poor prognostic factor in EC. The Tfh-based classification distinguishes immune characteristics and predicts ICI efficacy. A nomogram based on Tfh-related risk score accurately predicted the prognosis of patients with EC, demonstrating superior performance to TCGA-based classification.
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| 19. |
- Dareng, EO, et al.
(författare)
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Polygenic risk modeling for prediction of epithelial ovarian cancer risk
- 2022
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Ingår i: European journal of human genetics : EJHG. - : Springer Science and Business Media LLC. - 1476-5438 .- 1018-4813. ; 30:3, s. 349-362
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Tidskriftsartikel (refereegranskat)abstract
- Polygenic risk scores (PRS) for epithelial ovarian cancer (EOC) have the potential to improve risk stratification. Joint estimation of Single Nucleotide Polymorphism (SNP) effects in models could improve predictive performance over standard approaches of PRS construction. Here, we implemented computationally efficient, penalized, logistic regression models (lasso, elastic net, stepwise) to individual level genotype data and a Bayesian framework with continuous shrinkage, “select and shrink for summary statistics” (S4), to summary level data for epithelial non-mucinous ovarian cancer risk prediction. We developed the models in a dataset consisting of 23,564 non-mucinous EOC cases and 40,138 controls participating in the Ovarian Cancer Association Consortium (OCAC) and validated the best models in three populations of different ancestries: prospective data from 198,101 women of European ancestries; 7,669 women of East Asian ancestries; 1,072 women of African ancestries, and in 18,915 BRCA1 and 12,337 BRCA2 pathogenic variant carriers of European ancestries. In the external validation data, the model with the strongest association for non-mucinous EOC risk derived from the OCAC model development data was the S4 model (27,240 SNPs) with odds ratios (OR) of 1.38 (95% CI: 1.28–1.48, AUC: 0.588) per unit standard deviation, in women of European ancestries; 1.14 (95% CI: 1.08–1.19, AUC: 0.538) in women of East Asian ancestries; 1.38 (95% CI: 1.21–1.58, AUC: 0.593) in women of African ancestries; hazard ratios of 1.36 (95% CI: 1.29–1.43, AUC: 0.592) in BRCA1 pathogenic variant carriers and 1.49 (95% CI: 1.35–1.64, AUC: 0.624) in BRCA2 pathogenic variant carriers. Incorporation of the S4 PRS in risk prediction models for ovarian cancer may have clinical utility in ovarian cancer prevention programs.
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| 24. |
- Huang, WK, et al.
(författare)
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Heterogeneity of Metabolic Vulnerability in Imatinib -Resistant Gastrointestinal Stromal Tumor
- 2020
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Ingår i: Cells. - : MDPI AG. - 2073-4409. ; 9:6
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Tidskriftsartikel (refereegranskat)abstract
- Metabolic reprogramming is a hallmark of cancer cells in response to targeted therapy. Decreased glycolytic activity with enhanced mitochondrial respiration secondary to imatinib has been shown in imatinib-sensitive gastrointestional stromal tumors (GIST). However, the role of energy metabolism in imatinib-resistant GIST remains poorly characterized. Here, we investigated the effect of imatinib treatment on glycolysis and oxidative phosphorylation (OXPHOS), as well as the effect of inhibition of these energy metabolisms on cell viability in imatinib-resistant and -sensitive GIST cell lines. We observed that imatinib treatment increased OXPHOS in imatinib-sensitive, but not imatinib-resistant, GIST cells. Imatinib also reduced the expression of mitochondrial biogenesis activators (peroxisome proliferator-activated receptor coactivator-1 alpha (PGC1α), nuclear respiratory factor 2 (NRF2), and mitochondrial transcription factor A (TFAM)) and mitochondrial mass in imatinib-sensitive GIST cells. Lower TFAM levels were also observed in imatinib-sensitive GISTs than in tumors from untreated patients. Using the Seahorse system, we observed bioenergetics diversity among the GIST cell lines. One of the acquired resistant cell lines (GIST 882R) displayed a highly metabolically active phenotype with higher glycolysis and OXPHOS levels compared with the parental GIST 882, while the other resistant cell line (GIST T1R) had a similar basal glycolytic activity but lower mitochondrial respiration than the parental GIST T1. Further functional assays demonstrated that GIST 882R was more vulnerable to glycolysis inhibition than GIST 882, while GIST T1R was more resistant to OXPHOS inhibition than GIST T1. These findings highlight the diverse energy metabolic adaptations in GIST cells that allow them to survive upon imatinib treatment and reveal the potential of targeting the metabolism for GIST therapy.
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| 25. |
- Huang, WK, et al.
(författare)
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Imatinib Regulates miR-483-3p and Mitochondrial Respiratory Complexes in Gastrointestinal Stromal Tumors
- 2021
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Ingår i: International journal of molecular sciences. - : MDPI AG. - 1422-0067. ; 22:19
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Tidskriftsartikel (refereegranskat)abstract
- Metabolic adaptation to increased oxidative phosphorylation (OXPHOS) has been found in gastrointestinal stromal tumor (GIST) upon imatinib treatment. However, the underlying mechanism of imatinib-induced OXPHOS is unknown. Discovering molecules that mediate imatinib-induced OXPHOS may lead to the development of therapeutic strategies synergizing the efficacy of imatinib. In this study, we explored the role of microRNAs in regulating OXPHOS in GIST upon imatinib treatment. Using a microarray approach, we found that miR-483-3p was one of the most downregulated miRNAs in imatinib-treated tumors compared to untreated tumors. Using an extended series of GIST samples, we further validated the downregulation of miR-483-3p in imatinib-treated GIST samples by RT-qPCR. Using both gain- and loss-of-function experiments, we showed that miR-483-3p could regulate mitochondrial respiratory Complex II expression, suggesting its role in OXPHOS regulation. Functionally, miR-483-3p overexpression could rescue imatinib-induced cell death. These findings provide the molecular link for imatinib-induced OXPHOS expression and the biological role of miR-483-3p in regulating cell viability upon imatinib treatment.
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