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The genomics of primary prostate cancer differ from those of metastatic castration-resistant prostate cancer (mCRPC). We studied genomic aberrations in primary prostate cancer biopsies from patients who developed mCRPC, also studying matching, same-patient, diagnostic, and mCRPC biopsies following treatment. We profiled 470 treatment-naive prostate cancer diagnostic biopsies and, for 61 cases, mCRPC biopsies, using targeted and low-pass whole-genome sequencing (n = 52). Descriptive statistics were used to summarize mutation and copy number profile. Prevalence was compared using Fisher's exact test. Survival correlations were studied using log-rank test. TP53 (27%) and PTEN (12%) and DDR gene defects (BRCA2 7%; CDK12 5%; ATM 4%) were commonly detected. TP53, BRCA2, and CDK12 mutations were markedly more common than described in the TCGA cohort. Patients with RB1 loss in the primary tumor had a worse prognosis. Among 61 men with matched hormone-naive and mCRPC biopsies, differences were identified in AR, TP53, RB1, and PI3K/AKT mutational status between same-patient samples. In conclusion, the genomics of diagnostic prostatic biopsies acquired from men who develop mCRPC differ from those of the nonlethal primary prostatic cancers. RB1/TP53/AR aberrations are enriched in later stages, but the prevalence of DDR defects in diagnostic samples is similar to mCRPC.

The clinical relevance of the colorectal cancer serrated pathway is evident, but the screening of serrated lesions remains challenging. We aimed to characterize the serum methylome of the serrated pathway and to evaluate circulating cell‐free DNA (cfDNA) methylomes as a potential source of biomarkers for the non‐invasive detection of serrated lesions. We collected serum samples from individuals with serrated adenocarcinoma (SAC), traditional serrated adenomas, sessile serrated lesions, hyperplastic polyps and individuals with no colorectal findings. First, we quantified cfDNA methylation with the MethylationEPIC array. Then, we compared the methylation profiles with tissue and serum datasets. Finally, we evaluated the utility of serum cfDNA methylation biomarkers. We identified a differential methylation profile able to distinguish high‐risk serrated lesions from no serrated neoplasia, showing concordance with tissue methylation from SAC and sessile serrated lesions. Serum methylation profiles are pathway‐specific, clearly separating serrated lesions from conventional adenomas. The combination of ninjurin 2 (NINJ2) and glutamate‐rich 1 (ERICH1) methylation discriminated high‐risk serrated lesions and SAC with 91.4% sensitivity (64.4% specificity), while zinc finger protein 718 (ZNF718) methylation reported 100% sensitivity for the detection of SAC (96% specificity). This is the first study exploring the serum methylome of serrated lesions. Differential methylation of cfDNA can be used for the non‐invasive detection of colorectal serrated lesions. We analyzed the serum methylome of precursory lesions of the colorectal cancer serrated pathway and found a differential methylation profile between high‐risk serrated lesions and no serrated neoplasia. Since the methylation profiles in serum cfDNA are pathway‐specific at early stages, they may serve as a source of non‐invasive biomarkers for the detection of serrated lesions in screening programs.

Background: Some genetic polymorphisms (SNPs) have been proposed as predictors for different colorectal cancer (CRC) outcomes. This work aims to assess their performance in our cohort and find new SNPs associated with them. Methods: A total of 833 CRC cases were analyzed for seven outcomes, including the use of chemotherapy, and stratified by tumor location and stage. The performance of 63 SNPs was assessed using a generalized linear model and area under the receiver operating characteristic curve, and local SNPs were detected using logistic regressions. Results: In total 26 of the SNPs showed an AUC > 0.6 and a significant association (p < 0.05) with one or more outcomes. However, clinical variables outperformed some of them, and the combination of genetic and clinical data showed better performance. In addition, 49 suggestive (p < 5 × 10−6) SNPs associated with one or more CRC outcomes were detected, and those SNPs were located at or near genes involved in biological mechanisms associated with CRC. Conclusions: Some SNPs with clinical data can be used in our population as predictors of some CRC outcomes, and the local SNPs detected in our study could be feasible markers that need further validation as predictors.

Although the genetic contribution to colorectal cancer (CRC) has been studied in various populations, studies on the applicability of available genetic information in the Basque population are scarce. In total, 835 CRC cases and 940 controls from the Basque population were genotyped and genome-wide association studies were carried out. Mendelian Randomization analyses were used to discover the effect of modifiable risk factors and microbiota on CRC. In total, 25 polygenic risk score models were evaluated to assess their performance in CRC risk calculation. Moreover, 492 inflammatory bowel disease cases were used to assess whether that genetic information would not confuse both conditions. Five suggestive (p < 5 × 10−6) loci were associated with CRC risk, where genes previously associated with CRC were located (e.g., ABCA12, ATIC or ERBB4). Moreover, the analyses of CRC locations detected additional genes consistent with the biology of CRC. The possible contribution of cholesterol, BMI, Firmicutes and Cyanobacteria to CRC risk was detected by Mendelian Randomization. Finally, although polygenic risk score models showed variable performance, the best model performed correctly regardless of the location and did not misclassify inflammatory bowel disease cases. Our results are consistent with CRC biology and genetic risk models and could be applied to assess CRC risk in the Basque population.