David Robinson’s Post

A landmark new University of Oxford study of proteomic markers for 19 cancer types in the UK biobank by the has identified 182 proteins that may be used for early detection. Detection was done with Olink Proteomics which (antitrust permitting 😳) will soon be acquired by Thermo Fisher Scientific. I know from personal experience how careful Thermo is with M&A dollars, so they must have conviction to be paying $3.1B for Olink. Further proof (if there was any need) that the future of MCED is multiomic. (Also, in my opinion, evidence for proteomics being the next genomics as we move focus from genetic cause to clinical effect). "In this large prospective study of 1463 proteins with the risk of up to 19 cancers, we identified 371 plasma protein markers of cancer risk, including 107 that were associated with cancer diagnosed more than seven years after blood draw and many that also had support from complementary genetic analyses, which may suggest a role in aetiology. Furthermore, 182 proteins were strongly associated with diagnosis within three years, suggesting potential relevance as biomarkers for early detection."

The continuous advancement of the life science tools will reveal the paths between genomics and proteomics, impacting patient care.

The UK Biobank's availability of protein measurements and whole exome sequence data has enabled new discoveries in cancer research. A recent study investigated 1463 plasma proteins and their associations with 19 cancers and 9 cancer subsites in UK Biobank participants over an average 12-year follow-up. The results identified 618 protein-cancer associations, including some detectable more than seven years before cancer diagnosis. Genetic analyses provided supportive evidence for 29 of these associations, with four showing strong support from long time-to-diagnosis and both cis-pQTL and exGS analyses. The study's findings suggest a possible role of blood proteins in cancer development and may inform future cancer prevention strategies. Read more about this study in the link below. #cancerresearch #UKBiobank #proteomics #genetics

The UK Biobank's extensive data on protein measurements and whole exome sequences is a treasure trove for researchers. This recent study leveraged this resource to uncover potential links between plasma proteins and cancer risk. After analyzing 1463 proteins and their association with 19 different cancers, they've identified 618 potential protein-cancer associations. Notably, 107 of these associations were detectable for cases diagnosed more than seven years post blood draw. This long-term analysis, coupled with genetic approaches like cis-pQTL and exome-wide protein genetic scores, has revealed promising insights. For instance, proteins such as CD74 and TNFRSF1B with non-Hodgkin lymphoma, ADAM8 with leukemia, and SFTPA2 with lung cancer, show potential roles in cancer development. These findings not only advance our understanding of cancer but also highlight the predictive potential of blood proteins, opening new avenues for early detection and prevention strategies p/b University of Oxford, Queen's University Belfast, Keren Papier, Kezia Gaitskell, Trishna Desai, Chibuzor Ogamba, Mahboubeh Parsaeian, Gillian Reeves, Karl Smith Byrne #CancerResearch #Multiomics #UKBiobank https://lnkd.in/gVBA58bx

We are starting to learn how to treat earlier #GCLiveForeverClub

We are at a turning point in health research. This is what access to large datasets can do to understand, diagnose, treat and prevent disease.

Proteins in blood could provide early cancer warning ‘by more than seven years’. A study in Nature from the UK Biobank identifies 618 proteins linked to 19 types of #cancer, which could lead to much earlier detection. Really intriguing work from University of Oxford and funded by Cancer Research UK (CRUK) studied blood samples from more than 44,000 people in the UK Biobank, including over 4,900 people who subsequently had a cancer diagnosis. They compared the proteins of people who did and did not go on to be diagnosed with cancer and identified 618 proteins linked to 19 types of cancer, including colon, lung, non-Hodgkin lymphoma and liver malignancies. This article from The Guardian has a good overview: https://lnkd.in/gyZUUVdv Here is the Nature publication: https://lnkd.in/geFCGsyg For Pancreatic Cancer: recent work showed that a #microRNA based liquid biopsy developed at the City of Hope when combined their blood test for CA19-9,  accurately identified 97% of people with early-stage #pancreaticcancer. Presented at #AACR https://lnkd.in/gBz-gHpV The future of early, proactive #diagnostics (especially for early detection at 'Stage 0' cancer when intervention can save lives, morbidity and costs) will increasingly be multimodal (from blood proteins, DNA, and the 'immunome', to digital biomarkers). #earlydetection #digitalhealth #oncology #diagnosis #pharma #biobank #proteomics

Exciting new cancer biomarker study (Olink) using the UK Biobank. Identifying cancer risks several years ahead! Nature Communications Abstract "The availability of protein measurements and whole exome sequence data in the UK Biobank enables investigation of potential observational and genetic protein-cancer risk associations. We investigated associations of 1463 plasma proteins with incidence of 19 cancers and 9 cancer subsites in UK Biobank participants (average 12 years follow-up). Emerging protein-cancer associations were further explored using two genetic approaches, cis-pQTL and exome-wide protein genetic scores (exGS). We identify 618 protein-cancer associations, of which 107 persist for cases diagnosed more than seven years after blood draw, 29 of 618 were associated in genetic analyses, and four had support from long time-to-diagnosis ( > 7 years) and both cis-pQTL and exGS analyses: CD74 and TNFRSF1B with NHL, ADAM8 with leukemia, and SFTPA2 with lung cancer. We present multiple blood protein-cancer risk associations, including many detectable more than seven years before cancer diagnosis and that had concordant evidence from genetic analyses, suggesting a possible role in cancer development.” UK Biobank #cancer #biomarkers #proteomics #ukbiobank

📃Scientific paper: Causal associations between thyroid cancer and IgA nephropathy: a Mendelian randomization study Abstract: Background The incidence of kidney disease caused by thyroid cancer is rising worldwide. Observational studies cannot recognize whether thyroid cancer is independently associated with kidney disease. We performed the Mendelian randomization (MR) approach to genetically investigate the causality of thyroid cancer on immunoglobulin A nephropathy (IgAN). Methods and results We explored the causal effect of thyroid cancer on IgAN by MR analysis. Fifty-two genetic loci and single nucleotide polymorphisms were related to thyroid cancer. The primary approach in this MR analysis was the inverse variance weighted (IVW) method, and MR‒Egger was the secondary method. Weighted mode and penalized weighted median were used to analyze the sensitivity. In this study, the random-effect IVW models showed the causal impact of genetically predicted thyroid cancer across the IgAN risk (OR, 1.191; 95% CI, 1.131–1.253, P  < 0.001). Similar results were also obtained in the weighted mode method (OR, 1.048; 95% CI, 0.980–1.120, P  = 0.179) and penalized weighted median (OR, 1.185; 95% CI, 1.110–1.264, P  < 0.001). However, the MR‒Egger method revealed that thyroid cancer decreased the risk of IgAN, but this difference was not significant (OR, 0.948; 95% CI, 0.855–1.051, P  = 0.316). The leave-one-out sensitivity analysis did not reveal the driving influence of any individual SNP on the association between thyroid cancer and IgAN. Conclusion The IVW model indicated a significant causality... Continued on ES/IODE ➡️ https://etcse.fr/togjm ------- If you find this interesting, feel free to follow, comment and share. We need your help to enhance our visibility, so that our platform continues to serve you.

📃Scientific paper: Causal associations between thyroid cancer and IgA nephropathy: a Mendelian randomization study Abstract: Background The incidence of kidney disease caused by thyroid cancer is rising worldwide. Observational studies cannot recognize whether thyroid cancer is independently associated with kidney disease. We performed the Mendelian randomization (MR) approach to genetically investigate the causality of thyroid cancer on immunoglobulin A nephropathy (IgAN). Methods and results We explored the causal effect of thyroid cancer on IgAN by MR analysis. Fifty-two genetic loci and single nucleotide polymorphisms were related to thyroid cancer. The primary approach in this MR analysis was the inverse variance weighted (IVW) method, and MR‒Egger was the secondary method. Weighted mode and penalized weighted median were used to analyze the sensitivity. In this study, the random-effect IVW models showed the causal impact of genetically predicted thyroid cancer across the IgAN risk (OR, 1.191; 95% CI, 1.131–1.253, P  < 0.001). Similar results were also obtained in the weighted mode method (OR, 1.048; 95% CI, 0.980–1.120, P  = 0.179) and penalized weighted median (OR, 1.185; 95% CI, 1.110–1.264, P  < 0.001). However, the MR‒Egger method revealed that thyroid cancer decreased the risk of IgAN, but this difference was not significant (OR, 0.948; 95% CI, 0.855–1.051, P  = 0.316). The leave-one-out sensitivity analysis did not reveal the driving influence of any individual SNP on the association between thyroid cancer and IgAN. Conclusion The IVW model indicated a significant causality... Continued on ES/IODE ➡️ https://etcse.fr/togjm ------- If you find this interesting, feel free to follow, comment and share. We need your help to enhance our visibility, so that our platform continues to serve you.