Biomedical subjects

Sandra Perdomo

Publications and source records attributed to Sandra Perdomo.

4 recordsLinked to original sources

PubMed2026

Identification and validation of a previously missed mutational signature in colorectal cancer.

Mutational signature analysis has enhanced our understanding of mutagenic processes. In a recent study, we analyzed 802 microsatellite-stable colorectal cancers (CRC) and identified a de novo signature, SBS_D, which was decomposed into SBS18. Here, we re-evaluate this decomposition and provide evidence that SBS_D represents a distinct mutational process from SBS18. Through an analysis of 2,616 CRCs across three independent cohorts, we demonstrate that SBS_D is consistently present, suggesting this signature may have been previously overlooked. We illustrate that the pattern of SBS_D better aligns with signatures associated with deficiencies in DNA repair, despite evidence that SBS_D is not driven by canonical defects in these DNA repair pathways. Overall, this study identifies a previously unrecognized mutational signature in DNA repair-proficient CRC and proposes that its etiology may be linked to DNA repair infidelity emerging late in tumor development. SBS_D has been submitted to the COSMIC database and provisionally designated as SBS111.

Colorectal Neoplasms↗

PubMed2026

Analysis of structure and conservation for supporting functional evaluation of PMS2 missense variants.

Germline defects in mismatch repair (MMR) genes are known to significantly increase the risk of developing certain types of cancers, notably colorectal and endometrial cancers. These conditions are characterized under Lynch syndrome. Accurate diagnosis of this predisposition, along with meaningful predictive testing for family members, necessitates the identification of pathogenic variants. However, classifying small coding genetic variants identified in cancer patients is very challenging, specifically in the case of PMS2 variants, since PMS2 pathogenic variants display a lower penetrance and less severe phenotype and therefore a lower tumor burden in affected families. We have assembled clinical data on four PMS2 missense variants of uncertain significance (VUS) identified in 23 patients (p.(Asp286Gly), p.(Asn335Ser), p.(Ile679Thr) and p.(Arg799Trp)). For these variants, functional testing was performed (RNA splicing, protein stability and catalytic activity). Since many protein ortholog sequences and accurate predictive models from AlphaFold2 are available, we also included a systematic analysis of residue conservation and structural role (ConStruct assessment). Overall, our findings indicate that p.(Asp286Gly) and p.(Arg799Trp) behave similarly to wild-type PMS2 and are thus probably neutral. In contrast, p.(Asn335Ser) and p.(Ile679Thr) conferred defects in protein expression or MMR activity. These could be explained by the relevant roles of these amino acids in MLH1-PMS2-N-terminal dimerization (p.Asn335) and C-terminal dimerization (p.Ile679). Our data thus suggest that p.(Asp286Gly) and p.(Arg799Trp) are benign, while the tumor risk in the other two variants remains to be established. Taken together, we suggest roadmaps for the individualized evaluation of difficult uncertain variants by comprising information from all available sources.

Humans↗

PubMed2025

SPARKI: a tool for the statistical analysis of pathogen identification results.

MOTIVATION: Many pathogen identification and microbiome analysis tools have been developed in recent years, with Kraken 2 being one of the most popular. While tools downstream of Kraken 2 can assist in the interpretation of its outputs, a statistical framework to assess the likelihood that a taxon/organism is present in a single sample alongside an automated end-to-end analysis pipeline has not yet been fully implemented. RESULTS: Here, we introduce SPARKI, an R package that performs statistical analysis of Kraken 2 outputs and aids in the identification of pathogens present in next-generation sequencing samples. SPARKI adds to the field by bringing a probabilistic view to Kraken 2 data, serving as a discovery tool and complementing other methods such as KrakenTools, Bracken, and Pavian. AVAILABILITY AND IMPLEMENTATION: SPARKI code is available on GitHub at https://github.com/team113sanger/sparki. SPARKI is also part of an end-to-end pathogen identification pipeline, sparki-nf, which is available at https://github.com/team113sanger/sparki-nf. An additional pipeline for further exploration and validation of SPARKI results is also available at https://github.com/team113sanger/map-to-genome.

Software↗

PubMed2025

Identification and Validation of a Previously Missed Mutational Signature in Colorectal Cancer.

Mutational signature analysis has greatly enhanced our understanding of the mutagenic processes found in cancer and normal tissues. As part of a recent study, we analyzed 802 treatment-naïve, microsatellite-stable colorectal cancers (CRC) and identified a de novo signature, SBS_D, which was conservatively decomposed into SBS18, a signature associated with reactive oxygen species. Here, we re-evaluate this decomposition and provide evidence that SBS_D represents a distinct mutational process from that of SBS18. Through an independent analysis of 2,616 whole-genome sequenced microsatellite-stable CRCs across three distinct cohorts, we demonstrate that SBS_D is consistently present at a similar prevalence, suggesting that this signature may have been previously overlooked. Using a naïve decomposition approach, we demonstrate that the pattern of SBS_D better aligns with signatures previously associated with deficiencies in DNA polymerase delta (POLD1) proofreading and mismatch repair. However, multiple lines of evidence, including the absence of pathogenic mutations in the exonuclease domain of POLD1 or in mismatch repair-associated genes, indicate that SBS_D is not driven by canonical defects in these DNA repair pathways. Overall, this study identifies a previously unrecognized mutational signature in microsatellite-stable CRC and proposes that its etiology may be linked to DNA repair infidelity emerging late in tumor development in samples without canonical defects in DNA repair pathways.

Journal Article↗