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- Erice, Oihane, et al.
(author)
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LAMC2 regulates key transcriptional and targetable effectors to support pancreatic cancer growth
- 2023
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In: Clinical Cancer Research. - : American Association for Cancer Research (AACR). - 1078-0432 .- 1557-3265. ; 29:6, s. 1137-1154
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Journal article (peer-reviewed)abstract
- PURPOSE: The identification of pancreatic ductal adenocarcinoma (PDAC) dysregulated genes may unveil novel molecular targets entering inhibitory strategies. Laminins are emerging as potential targets in PDAC given their role as diagnostic and prognostic markers. Here, we investigated the cellular, functional, and clinical relevance of LAMC2 and its regulated network, with the ultimate goal of identifying potential therapies.EXPERIMENTAL DESIGN: LAMC2 expression was analyzed in PDAC tissues, a panel of human and mouse cell lines, and a genetically engineered mouse model. Genetic perturbation in 2D, 3D, and in vivo allograft and xenograft models was done. Expression profiling of a LAMC2 network was performed by RNA-sequencing, and publicly available gene expression datasets from experimental and clinical studies examined to query its human relevance. Dual inhibition of pharmacologically targetable LAMC2-regulated effectors was investigated.RESULTS: LAMC2 was consistently upregulated in human and mouse experimental models as well as in human PDAC specimens, and associated with tumor grade and survival. LAMC2 inhibition impaired cell cycle, induced apoptosis, and sensitized PDAC to MEK1/2 inhibitors (MEK1/2i). A LAMC2-regulated network was featured in PDAC, including both classical and quasi-mesenchymal subtypes, and contained downstream effectors transcriptionally shared by the KRAS signaling pathway. LAMC2 regulated a functional FOSL1-AXL axis via AKT phosphorylation. Furthermore, genetic LAMC2 or pharmacological AXL inhibition elicited a synergistic antiproliferative effect in combination with MEK1/2is that was consistent across 2D and 3D human and mouse PDAC models, including primary patient-derived organoids.CONCLUSIONS: LAMC2 is a molecular target in PDAC that regulates a transcriptional network that unveils a dual drug combination for cancer treatment.
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- Sampson, Joshua N., et al.
(author)
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Analysis of Heritability and Shared Heritability Based on Genome-Wide Association Studies for 13 Cancer Types
- 2015
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In: Journal of the National Cancer Institute. - : Oxford University Press (OUP). - 0027-8874 .- 1460-2105. ; 107:12
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Journal article (peer-reviewed)abstract
- Background: Studies of related individuals have consistently demonstrated notable familial aggregation of cancer. We aim to estimate the heritability and genetic correlation attributable to the additive effects of common single-nucleotide polymorphisms (SNPs) for cancer at 13 anatomical sites. Methods: Between 2007 and 2014, the US National Cancer Institute has generated data from genome-wide association studies (GWAS) for 49 492 cancer case patients and 34 131 control patients. We apply novel mixed model methodology (GCTA) to this GWAS data to estimate the heritability of individual cancers, as well as the proportion of heritability attributable to cigarette smoking in smoking-related cancers, and the genetic correlation between pairs of cancers. Results: GWAS heritability was statistically significant at nearly all sites, with the estimates of array-based heritability, h(l)(2), on the liability threshold (LT) scale ranging from 0.05 to 0.38. Estimating the combined heritability of multiple smoking characteristics, we calculate that at least 24% (95% confidence interval [CI] = 14% to 37%) and 7% (95% CI = 4% to 11%) of the heritability for lung and bladder cancer, respectively, can be attributed to genetic determinants of smoking. Most pairs of cancers studied did not show evidence of strong genetic correlation. We found only four pairs of cancers with marginally statistically significant correlations, specifically kidney and testes (rho = 0.73, SE = 0.28), diffuse large B-cell lymphoma (DLBCL) and pediatric osteosarcoma (rho = 0.53, SE = 0.21), DLBCL and chronic lymphocytic leukemia (CLL) (rho = 0.51, SE = 0.18), and bladder and lung (rho = 0.35, SE = 0.14). Correlation analysis also indicates that the genetic architecture of lung cancer differs between a smoking population of European ancestry and a nonsmoking Asian population, allowing for the possibility that the genetic etiology for the same disease can vary by population and environmental exposures. Conclusion: Our results provide important insights into the genetic architecture of cancers and suggest new avenues for investigation.
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- Wang, Zhaoming, et al.
(author)
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Imputation and subset-based association analysis across different cancer types identifies multiple independent risk loci in the TERT-CLPTM1L region on chromosome 5p15.33
- 2014
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In: Human Molecular Genetics. - : Oxford University Press (OUP). - 0964-6906 .- 1460-2083. ; 23:24, s. 6616-6633
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Journal article (peer-reviewed)abstract
- Genome-wide association studies (GWAS) have mapped risk alleles for at least 10 distinct cancers to a small region of 63 000 bp on chromosome 5p15.33. This region harbors the TERT and CLPTM1L genes; the former encodes the catalytic subunit of telomerase reverse transcriptase and the latter may play a role in apoptosis. To investigate further the genetic architecture of common susceptibility alleles in this region, we conducted an agnostic subset-based meta-analysis (association analysis based on subsets) across six distinct cancers in 34 248 cases and 45 036 controls. Based on sequential conditional analysis, we identified as many as six independent risk loci marked by common single-nucleotide polymorphisms: five in the TERT gene (Region 1: rs7726159, P = 2.10 × 10(-39); Region 3: rs2853677, P = 3.30 × 10(-36) and PConditional = 2.36 × 10(-8); Region 4: rs2736098, P = 3.87 × 10(-12) and PConditional = 5.19 × 10(-6), Region 5: rs13172201, P = 0.041 and PConditional = 2.04 × 10(-6); and Region 6: rs10069690, P = 7.49 × 10(-15) and PConditional = 5.35 × 10(-7)) and one in the neighboring CLPTM1L gene (Region 2: rs451360; P = 1.90 × 10(-18) and PConditional = 7.06 × 10(-16)). Between three and five cancers mapped to each independent locus with both risk-enhancing and protective effects. Allele-specific effects on DNA methylation were seen for a subset of risk loci, indicating that methylation and subsequent effects on gene expression may contribute to the biology of risk variants on 5p15.33. Our results provide strong support for extensive pleiotropy across this region of 5p15.33, to an extent not previously observed in other cancer susceptibility loci.
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