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- Chen, Hongjie, et al.
(författare)
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Large-scale cross-cancer fine-mapping of the 5p15.33 region reveals multiple independent signals
- 2021
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Ingår i: Human Genetics and Genomics Advances. - : Cell Press. - 2666-2477. ; 2:3
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Tidskriftsartikel (refereegranskat)abstract
- Genome-wide association studies (GWASs) have identified thousands of cancer risk loci revealing many risk regions shared across multiple cancers. Characterizing the cross-cancer shared genetic basis can increase our understanding of global mechanisms of cancer development. In this study, we collected GWAS summary statistics based on up to 375,468 cancer cases and 530,521 controls for fourteen types of cancer, including breast (overall, estrogen receptor [ER]-positive, and ER-negative), colorectal, endometrial, esophageal, glioma, head/neck, lung, melanoma, ovarian, pancreatic, prostate, and renal cancer, to characterize the shared genetic basis of cancer risk. We identified thirteen pairs of cancers with statistically significant local genetic correlations across eight distinct genomic regions. Specifically, the 5p15.33 region, harboring the TERT and CLPTM1L genes, showed statistically significant local genetic correlations for multiple cancer pairs. We conducted a cross-cancer fine-mapping of the 5p15.33 region based on eight cancers that showed genome-wide significant associations in this region (ER-negative breast, colorectal, glioma, lung, melanoma, ovarian, pancreatic, and prostate cancer). We used an iterative analysis pipeline implementing a subset-based meta-analysis approach based on cancer-specific conditional analyses and identified ten independent cross-cancer associations within this region. For each signal, we conducted cross-cancer fine-mapping to prioritize the most plausible causal variants. Our findings provide a more in-depth understanding of the shared inherited basis across human cancers and expand our knowledge of the 5p15.33 region in carcinogenesis.
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- de Muynck, Ldan, et al.
(författare)
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Consensus Statement on the Use of Near-Infrared Fluorescence Imaging during Pancreatic Cancer Surgery Based on a Delphi Study: Surgeons' Perspectives on Current Use and Future Recommendations
- 2023
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Ingår i: Cancers. - : MDPI AG. - 2072-6694. ; 15:3
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Tidskriftsartikel (refereegranskat)abstract
- Simple Summary Despite the potential of fluorescence imaging during pancreatic cancer surgery, more research is needed to facilitate the approval of tumor-targeted probes, standardize imaging techniques, and most importantly, gain trust from surgeons. Despite advancements in the development of novel probes, preclinical research settings do not always accurately represent the surgical setting. This first-of-its-kind Delphi consensus survey highlights current experiences and attitudes towards fluorescence imaging during pancreatic cancer surgery, specifically from surgeon's perspectives. The results from this consensus survey highlight potential new directions for future research, which could facilitate the standardized use of fluorescence imaging during pancreatic surgery. Indocyanine green (ICG) is one of the only clinically approved near-infrared (NIR) fluorophores used during fluorescence-guided surgery (FGS), but it lacks tumor specificity for pancreatic ductal adenocarcinoma (PDAC). Several tumor-targeted fluorescent probes have been evaluated in PDAC patients, yet no uniformity or consensus exists among the surgical community on the current and future needs of FGS during PDAC surgery. In this first-published consensus report on FGS for PDAC, expert opinions were gathered on current use and future recommendations from surgeons' perspectives. A Delphi survey was conducted among international FGS experts via Google Forms. Experts were asked to anonymously vote on 76 statements, with >= 70% agreement considered consensus and >= 80% participation/statement considered vote robustness. Consensus was reached for 61/76 statements. All statements were considered robust. All experts agreed that FGS is safe with few drawbacks during PDAC surgery, but that it should not yet be implemented routinely for tumor identification due to a lack of PDAC-specific NIR tracers and insufficient evidence proving FGS's benefit over standard methods. However, aside from tumor imaging, surgeons suggest they would benefit from visualizing vasculature and surrounding anatomy with ICG during PDAC surgery. Future research could also benefit from identifying neuroendocrine tumors. More research focusing on standardization and combining tumor identification and vital-structure imaging would greatly improve FGS's use during PDAC surgery.
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- Fuhrmann, Martin, et al.
(författare)
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Super-Resolution Microscopy Opens New Doors to Life at the Nanoscale
- 2022
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Ingår i: Journal of Neuroscience. - : Society for Neuroscience. - 0270-6474 .- 1529-2401. ; 42:45, s. 8488-8497
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Tidskriftsartikel (refereegranskat)abstract
- Super-resolution fluorescence microscopy holds tremendous potential for discovery in neuroscience. Much of the molecular machinery and anatomic specializations that give rise to the unique and bewildering electrochemical activity of neurons are nanoscale by design, ranging somewhere between 1 nm and 1 lm. It is at this scale where most of the unknown and exciting action is and where cell biolo-gists flock to in their dreams, but it was off limits for light microscopy until recently. While the optical principles of super-resolution microscopy are firmly established by now, the technology continues to advance rapidly in many crucial areas, enhancing its perform-ance and reliability, and making it more accessible and user-friendly, which is sorely needed. Indeed, super-resolution microscopy tech-niques are nowadays widely used for visualizing immunolabeled protein distributions in fixed or living cells. However, a great potential of super-resolution microscopy for neuroscience lies in shining light on the nanoscale structures and biochemical activities in live-tissue settings, which should be developed and harnessed much more fully. In this review, we will present several vivid examples based on STED and RESOLFT super-resolution microscopy, illustrating the possibilities and challenges of nano-imaging in vivo to pique the interest of tech-developers and neurobiologists alike. We will cover recent technical progress that is facilitating in vivo applications, and share new biological insights into the nanoscale mechanisms of cellular communication between neurons and glia.
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- Hess, Timo, et al.
(författare)
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Dissecting the genetic heterogeneity of gastric cancer
- 2023
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Ingår i: EBioMedicine. - : Elsevier. - 2352-3964. ; 92
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Tidskriftsartikel (refereegranskat)abstract
- Background: Gastric cancer (GC) is clinically heterogenous according to location (cardia/non-cardia) and histopathology (diffuse/intestinal). We aimed to characterize the genetic risk architecture of GC according to its subtypes. Another aim was to examine whether cardia GC and oesophageal adenocarcinoma (OAC) and its precursor lesion Barrett's oesophagus (BO), which are all located at the gastro-oesophageal junction (GOJ), share polygenic risk architecture.Methods: We did a meta-analysis of ten European genome-wide association studies (GWAS) of GC and its subtypes. All patients had a histopathologically confirmed diagnosis of gastric adenocarcinoma. For the identification of risk genes among GWAS loci we did a transcriptome-wide association study (TWAS) and expression quantitative trait locus (eQTL) study from gastric corpus and antrum mucosa. To test whether cardia GC and OAC/BO share genetic aetiology we also used a European GWAS sample with OAC/BO.Findings: Our GWAS consisting of 5816 patients and 10,999 controls highlights the genetic heterogeneity of GC according to its subtypes. We newly identified two and replicated five GC risk loci, all of them with subtype-specific association. The gastric transcriptome data consisting of 361 corpus and 342 antrum mucosa samples revealed that an upregulated expression of MUC1, ANKRD50, PTGER4, and PSCA are plausible GC-pathomechanisms at four GWAS loci. At another risk locus, we found that the blood-group 0 exerts protective effects for non-cardia and diffuse GC, while blood-group A increases risk for both GC subtypes. Furthermore, our GWAS on cardia GC and OAC/BO (10,279 patients, 16,527 controls) showed that both cancer entities share genetic aetiology at the polygenic level and identified two new risk loci on the single-marker level.Interpretation: Our findings show that the pathophysiology of GC is genetically heterogenous according to location and histopathology. Moreover, our findings point to common molecular mechanisms underlying cardia GC and OAC/BO.
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- Lenz, Tobias L., et al.
(författare)
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Widespread non-additive and interaction effects within HLA loci modulate the risk of autoimmune diseases
- 2015
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Ingår i: Nature Genetics. - : Macmillan Publishers Ltd.. - 1061-4036 .- 1546-1718. ; 47:9, s. 1085-1090
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Tidskriftsartikel (refereegranskat)abstract
- Human leukocyte antigen (HLA) genes confer substantial risk for autoimmune diseases on a log-additive scale. Here we speculated that differences in autoantigen-binding repertoires between a heterozygote's two expressed HLA variants might result in additional non-additive risk effects. We tested the non-additive disease contributions of classical HLA alleles in patients and matched controls for five common autoimmune diseases: rheumatoid arthritis (n(cases) = 5,337), type 1 diabetes (T1D; n(cases) = 5,567), psoriasis vulgaris (n(cases) = 3,089), idiopathic achalasia (n(cases) = 727) and celiac disease (ncases = 11,115). In four of the five diseases, we observed highly significant, non-additive dominance effects (rheumatoid arthritis, P = 2.5 x 10(-12); T1D, P = 2.4 x 10(-10); psoriasis, P = 5.9 x 10(-6); celiac disease, P = 1.2 x 10(-87)). In three of these diseases, the non-additive dominance effects were explained by interactions between specific classical HLA alleles (rheumatoid arthritis, P = 1.8 x 10(-3); T1D, P = 8.6 x 10(-27); celiac disease, P = 6.0 x 10(-100)). These interactions generally increased disease risk and explained moderate but significant fractions of phenotypic variance (rheumatoid arthritis, 1.4%; T1D, 4.0%; celiac disease, 4.1%) beyond a simple additive model.
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- Lindström, Sara, et al.
(författare)
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Genome-wide analyses characterize shared heritability among cancers and identify novel cancer susceptibility regions
- 2023
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Ingår i: Journal of the National Cancer Institute. - : Oxford University Press. - 0027-8874 .- 1460-2105. ; 115:6, s. 712-732
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Tidskriftsartikel (refereegranskat)abstract
- BACKGROUND: The shared inherited genetic contribution to risk of different cancers is not fully known. In this study, we leverage results from 12 cancer genome-wide association studies (GWAS) to quantify pairwise genome-wide genetic correlations across cancers and identify novel cancer susceptibility loci.METHODS: We collected GWAS summary statistics for 12 solid cancers based on 376 759 participants with cancer and 532 864 participants without cancer of European ancestry. The included cancer types were breast, colorectal, endometrial, esophageal, glioma, head and neck, lung, melanoma, ovarian, pancreatic, prostate, and renal cancers. We conducted cross-cancer GWAS and transcriptome-wide association studies to discover novel cancer susceptibility loci. Finally, we assessed the extent of variant-specific pleiotropy among cancers at known and newly identified cancer susceptibility loci.RESULTS: We observed widespread but modest genome-wide genetic correlations across cancers. In cross-cancer GWAS and transcriptome-wide association studies, we identified 15 novel cancer susceptibility loci. Additionally, we identified multiple variants at 77 distinct loci with strong evidence of being associated with at least 2 cancer types by testing for pleiotropy at known cancer susceptibility loci.CONCLUSIONS: Overall, these results suggest that some genetic risk variants are shared among cancers, though much of cancer heritability is cancer-specific and thus tissue-specific. The increase in statistical power associated with larger sample sizes in cross-disease analysis allows for the identification of novel susceptibility regions. Future studies incorporating data on multiple cancer types are likely to identify additional regions associated with the risk of multiple cancer types.
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