Molecular portraits of colorectal cancer morphological regions

Abstract

Heterogeneity of colorectal carcinoma (CRC) represents a major hurdle towards personalized medicine. Efforts based on whole tumor profiling demonstrated that the CRC molecular subtypes were associated with specific tumor morphological patterns representing tumor subregions. We hypothesize that whole-tumor molecular descriptors depend on the morphological heterogeneity with significant impact on current molecular predictors. We investigated intra-tumor heterogeneity by morphology-guided transcriptomics to better understand the links between gene expression and tumor morphology represented by six morphological patterns (morphotypes): complex tubular, desmoplastic, mucinous, papillary, serrated, and solid/trabecular. Whole-transcriptome profiling by microarrays of 202 tumor regions (morphotypes, tumor-adjacent normal tissue, supportive stroma, and matched whole tumors) from 111 stage II-IV CRCs identified morphotype-specific gene expression profiles and molecular programs and differences in their cellular buildup. The proportion of cell types (fibroblasts, epithelial and immune cells) and differentiation of epithelial cells were the main drivers of the observed disparities with activation of EMT and TNF-α signaling in contrast to MYC and E2F targets signaling, defining major gradients of changes at molecular level. Several gene expression-based (including single-cell) classifiers, prognostic and predictive signatures were examined to study their behavior across morphotypes. Most exhibited important morphotype-dependent variability within same tumor sections, with regional predictions often contradicting the whole-tumor classification. The results show that morphotype-based tumor sampling allows the detection of molecular features that would otherwise be distilled in whole tumor profile, while maintaining histopathology context for their interpretation. This represents a practical approach at improving the reproducibility of expression profiling and, by consequence, of gene-based classifiers.

A quantitative tumor–wide analysis of morphological heterogeneity of colorectal adenocarcinoma

“…Our group ( Popovici et al, 2017 ) and later others ( Sirinukunwattana et al, 2021 ) managed to replicate the transcriptome-based molecular classification of CRC using automatic analysis of readily available high-resolution digital haematoxylin-eosin (H&E) slides. These results confirmed the close relationship between tumor morphology and coding transcriptome and were further strengthen by our recent analysis of the molecular programs associated with specific morphological patterns ( Budinská et al, 2023 ).…”

“…However, even prior to the CMS, our research indicated that the CRC transcriptome subtypes are linked to various morphological patterns ( Budinská et al, 2013 ). Having those patterns as a starting point, we later identified pattern-specific molecular programs in CRC ( Budinská et al, 2023 ). Hence, we wanted to analyze the whole spectrum of morphological heterogeneity by using both expert pathologist and AI-based methodology and by considering four slides per tumor (from different FFPE blocks).…”

“…Morphotypes were defined by mapping frequently occurring morphologies of CRC as described in our previous publications ( Budinská et al, 2013 ; Budinská et al, 2023 ). These overlap in part with the carcinoma subtypes as defined in WHO 2019 ( Organisation mondiale de la santé, 2019 ).…”

“…We decided to use the term morphotype to indicate ‘pure morphology’, whereas the WHO’s subtypes are (inherently) morphologically heterogeneous. The six morphotypes were (see also Figure 1 in ( Budinská et al, 2023 )):…”

“… Abstract Morphologic heterogeneity of colorectal adenocarcinoma (CRC) is poorly understood. Previously, we identified morphological patterns associated with CRC molecular subtypes, and showed that these patterns have distinct molecular motifs ( Budinská et al, 2023 ). Here, we evaluated the heterogeneity of these patterns across CRC.…”