Exome and Tissue-Associated Microbiota as Predictive Markers of Response to Neoadjuvant Treatment in Locally Advanced Rectal Cancer

Abstract

The clinical and pathological responses to multimodal neoadjuvant therapy in locally advanced rectal cancers (LARCs) remain unpredictable, and robust biomarkers are still lacking. Recent studies have shown that tumors present somatic molecular alterations related to better treatment response, and it is also clear that tumor-associated bacteria are modulators of chemotherapy and immunotherapy efficacy, therefore having implications for long-term survivorship and a good potential as the biomarkers of outcome. Here, we performed whole exome sequencing and 16S ribosomal RNA (rRNA) amplicon sequencing from 44 pre-treatment LARC biopsies from Argentinian and Brazilian patients, treated with neoadjuvant chemoradiotherapy or total neoadjuvant treatment, searching for predictive biomarkers of response (responders, n = 17; non-responders, n = 27). In general, the somatic landscape of LARC was not capable to predict a response; however, a significant enrichment in mutational signature SBS5 was observed in non-responders (p = 0.0021), as well as the co-occurrence of APC and FAT4 mutations (p < 0.05). Microbiota studies revealed a similar alpha and beta diversity of bacteria between response groups. Yet, the linear discriminant analysis (LDA) of effect size indicated an enrichment of Hungatella, Flavonifractor, and Methanosphaera (LDA score ≥3) in the pre-treatment biopsies of responders, while non-responders had a higher abundance of Enhydrobacter, Paraprevotella (LDA score ≥3) and Finegoldia (LDA score ≥4). Altogether, the evaluation of these biomarkers in pre-treatment biopsies could eventually predict a neoadjuvant treatment response, while in post-treatment samples, it could help in guiding non-operative treatment strategies.

Neoadjuvant treatment of rectal cancer: Where we are and where we are going

“…Other studies have examined the expression of specific genes and established a prognostic risk score model to predict the response to ChT[ 35 ]. The role of the microbiota has also been analyzed in neoadjuvant treatment response, and the presence of certain bacteria has been associated with a poorer response to treatment[ 36 ].…”

Role of the gut microbiota in dietary patterns rich in torularhodinviaOSA colon-targeted delivery

“…The QIIME2 and R-packages were used to analyze the microbial sparsity curves, Shannon diversity, Chao1 index, Bray-Curtis index, principal coordinate analysis (PCA), and random forest supervised learning models. 22 The PICRUSt2 software was used to predict the gut microbial genomic function via the KEGG database (https://huttenhower. sph.harvard.edu/galaxy/).…”