Reply to the discussion and comments of Azerêdo et al. (2023) and Schneider et al. (2023) on the paper by Magalhães et al. ‘Middle Jurassic multi-scale transgressive–regressive cycles: An example from the Lusitanian Basin’, The Depositional Record, 9, 174–202

cently published paper. The exchange of ideas, data and interpretation improves our knowledge and is the right way to discuss science\u27s advances. This reply considers the points raised by Azerêdo et al. (2023) and Schneider et al. (2023). In both manuscripts, these authors raised many issues about sedimentological and stratigraphic aspects that can be separated into two groups: (a) those related to the age of the studied succession; and (b) those assigning the studied succession to the Candeeiros Formation

An Integrated TCGA Pan-Cancer Clinical Data Resource to Drive High-Quality Survival Outcome Analytics

For a decade, The Cancer Genome Atlas (TCGA) program collected clinicopathologic annotation data along with multi-platform molecular profiles of more than 11,000 human tumors across 33 different cancer types. TCGA clinical data contain key features representing the democratized nature of the data collection process. To ensure proper use of this large clinical dataset associated with genomic features, we developed a standardized dataset named the TCGA Pan-Cancer Clinical Data Resource (TCGA-CDR), which includes four major clinical outcome endpoints. In addition to detailing major challenges and statistical limitations encountered during the effort of integrating the acquired clinical data, we present a summary that includes endpoint usage recommendations for each cancer type. These TCGA-CDR findings appear to be consistent with cancer genomics studies independent of the TCGA effort and provide opportunities for investigating cancer biology using clinical correlates at an unprecedented scale. Analysis of clinicopathologic annotations for over 11,000 cancer patients in the TCGA program leads to the generation of TCGA Clinical Data Resource, which provides recommendations of clinical outcome endpoint usage for 33 cancer types