P-281 Importance of tumor sampling in transcriptomics-based risk stratification

نویسندگان

چکیده

The variability of gene expression signatures across tumor sites has been previously documented [Stewart et al. 2017]. However, how this information can be exploited in practice is less obvious. To better understand the links between gene-based risk scores and sampling, we performed morphology-based RNA extraction studied scores' their relative prognostic value comparison with whole-tumor sampling. We deliberately avoided comparing to each other, since our data did not allow significant comparisons. From 99 colon tumors (hospital cohort), consecutive sections were used for morphological-region extraction. following morphological regions have manually annotated virtual slides macro-dissected: complex tubular, desmoplastic, mucinous, papillary, serrated solid trabecular. Additionally, a number adjacent normal stroma marked. increase statistical power, from same tissue section also considered grouped together according stromal tumoral content. ESTIMATE [Yoshihara 2013] was score content Cox regression analysis assess significance scores. 10 different computed on whole tumor, respectively. In total, 173 regional transcriptomics profiles obtained, patient ranking varied greatly (Spearman correlation -0.12 0.64), indicating wide range predictions. into stroma-rich (S) (e.g. desmoplastic) or cell-rich (T) serrated, trabecular) regions, respective general (7 out 10), performing either S T performance. multivariable analysis, including region scores, significantly than (respective p < 0.05) 5 other cases none them achieving significance. Interestingly, selecting worst prognosis among lead an overall stronger predictor S- T-region one. current limited cohort derivation validation novel, region-based score. varies morphotypes and, general, improved by more targeted Each had preference one type (tumor- stroma-rich), consequence resptective strategies. Consequently, morphology-guided construction may performance multi-region strategy prove most robust.

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ژورنال

عنوان ژورنال: Annals of Oncology

سال: 2022

ISSN: ['0923-7534', '1569-8041']

DOI: https://doi.org/10.1016/j.annonc.2022.04.370