Biology subjects

Pluta, J.

Publications and source records attributed to Pluta, J..

2 recordsLinked to original sources

bioRxiv2025

Harmonized Protocol for Subfield Segmentation in the Hippocampal Body on High-Resolution in vivo MRI from the Hippocampal Subfields Group (HSG)

Hippocampal subfields differentially develop and age, and they vary in vulnerability to neurodegenerative diseases. Innovation in high-resolution imaging has accelerated clinical research on human hippocampal subfields, but substantial differences in segmentation protocols impede comparisons of results across laboratories. The Hippocampal Subfields Group (HSG) is an international organization seeking to address this issue by developing a histologically-valid, reliable, and freely available segmentation protocol for high-resolution T2-weighted 3 tesla MRI (http://www.hippocampalsubfields.com). Here, we report the first portion of the protocol focused on subfields in the hippocampal body; protocols for the head and tail are in development. The body protocol includes definitions of the internal boundaries between subiculum, Cornu Ammonis (CA) 1-3 subfields, and dentate gyrus, in addition to the external boundaries of the hippocampus apart from surrounding white matter and cerebrospinal fluid. The segmentation protocol is based on a novel histological reference data set labeled by multiple expert neuroanatomists. With broad participation of the research community, we voted on the segmentation protocol via online survey, which included detailed protocol information, feasibility testing, demonstration videos, example segmentations, and labeled histology. All boundary definitions were rated as having high clarity and reached consensus agreement by Delphi procedure. The harmonized body protocol yielded high inter- and intra-rater reliability. In the present paper we report the procedures to develop and test the protocol, as well as the detailed procedures for manual segmentation using the harmonized protocol. The harmonized protocol will significantly facilitate cross-study comparisons and provide increased insight into the structure and function of hippocampal subfields across the lifespan and in neurodegenerative diseases.

neuroscience↗

bioRxiv2022

HRDex: a tool for deriving homologous recombination deficiency (HRD) scores from whole exome sequencing data

BackgroundBreast and ovarian tumors in patients with biallelic BRCA1 and BRCA2 mutations either by germline mutations accompanied by allele-specific loss of heterozygosity (LOH) or truncal somatic mutations respond to PARP inhibition. The repair of double stranded DNA breaks in tumors these tumors leads to homologous recombination deficiency (HRD), which can be measured using a variety of genomic and transcriptomic signatures. However, the optimal biomarker for BRCA deficiency is unknown. MethodsWe developed HRDex to determine HRD and its composite scores from allele specific copy number data analysis of whole exome sequencing (WES) data and examined the discriminatory ability of HRDex and other genomic and transcriptomic measures to identify BRCA deficiency in breast and ovarian tumors from The Cancer Genome Atlas (TCGA). ResultsHRDex scores have high correlation with SNP array based HRD scores in both breast and ovarian cancers. HRDex scores have high discriminatory accuracy to distinguish BRCA deficient breast tumors, similar to SNP array based scores (AUC 0.87 vs 0.90); however, discriminatory ability for ovarian tumors was lower (AUC 0.79 vs 0.90). HRD-LST had the best discriminatory ability of the three composite HRD scores. HRDex had higher discriminatory ability for identification of BRCA deficiency than RNA expression based scores (eCARD, tp53, RPS and PARPi7) in breast and ovarian tumors. Tumor mutational burden (TMB) was associated with BRCA deficiency in breast but not ovarian cancer. Combining HRDex score with mutational signature 3 modestly increased discriminatory ability for BRCA deficient breast and ovarian tumors (breast: AUC 0.90 vs 0.87; ovarian: AUC 0.83 vs 0.79). ConclusionsWES based HRD scores perform similarly to SNP array HRD scores, and better than other genomic or transcriptomic signatures, for identification of tumors with BRCA deficiency due to biallelic BRCA loss.

genomics↗