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MicroRNA expression in preoperative chemoradiotherapy for rectal cancer (LARC)

ABSTRACT: The incorporation of chemoradiation prior to resection of the tumour has revolutionized the management of locally advanced rectal cancer. However, a large proportion of these patients are resistant to preoperative treatment schedule. We recently reported that c-Myc gene expression correlates negatively with this resistance in patients with rectal cancer. In this study, we carried out integrated analysis of miRNA and mRNA expression profiling in 45 pre-treatment rectal tumour. Further, expression of miRNAs and c-Myc, and their relationship with clinicopathological factors and patient survival was analysed. As a result, we found that 12 miRNAs were differentially expressed between responder and non-responder rectal cancer patients. Functional classification revealed an association between differentially expressed miRNAs and c-Myc. Subsequent quantitative real-time PCR results showed that both, miRNA-148 and miRNA-375 levels were significantly lower in responder compared to non-responder patients. Notably, the higher level of miRNA-375 was significantly negatively correlated with c-Myc. These results suggest that miRNA-375 and its targeted c-Myc play an important role as predictive biomarker of response to neoadjuvant treatment in patients with locally advanced rectal cancer, but still not suitable for prognosis. Pre-treatment biopsies of 22 patients with LARC were prospectively collected and freshly frozen according to an institutional board-approved protocol. Tumour response was assessed in surgical specimens by pathological examination based on the semi-quantitative tumour regression grading (TRG) system described by Mandard in 1994[36]: TRG1 and TRG2 scores were considered responders, whereas TRG3, TRG4, and TRG5 were classified as non-responders. The inclusion criteria were: histologically proven rectal tumour at a clinical stage UICC II-III (cT3-4/and or N positive), following endorectal ultrasound and/or MRI scan. Patients were excluded if they had the tumour located above 13 cm from the anal verge by rigid rectoscopy, synchronic colonic cancer assessed by colonoscopy, distant metastases by 18FDG PET-CT scan, and suspicion of hereditary colorectal cancer. All patients subsequently received a total dose of 50.4Gy of radiation (28 fractions of 1.8Gy) associated with capecitabine (oral form of 5-FU) with or without oxaliplatine, according to our Hospital Clinical Practice Guidelines. Standardized Surgery was performed, including total mesorectal excision, following an interval of 8-10 weeks after completion of CT/RT.

ORGANISM(S): Homo sapiens

PROVIDER: GSE98959 | GEO | 2017/05/17

SECONDARY ACCESSION(S): PRJNA386933

REPOSITORIES: GEO

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Project description:Although preoperative chemoradiotherapy (CRT) and surgical mesorectal resection is the standard of care for locally advanced rectal carcinomas, it is still difficult to predict which patients will respond to treatment. We explored how differential stromal transcriptomic profiles from microdissected pretreatment rectal biopsies can be used to define an immunohistochemical score based on two CAF-specific proteins for predicting neoadjuvant treatment response. The analysis of differentially expressed genes (DEGs) of stroma and tumour glands from responder and non-responder patients shows that most changes were associated with the stromal compartment. Gene ontology analysis revealed that the DEGs codify mainly for extracellular matrix and ribosomal components. We built a CAF-specific classifier with genes showing monotonic changes in expression according to the tumour regression grade (coefficient >1; FN1, COL3A1, COL1A1, MMP2 and IGFBP5). These are the genes that display the biggest a priori differences in expression between non-responder and responder stroma. We translated these five genes at the protein level by means of immunohistochemical staining in a cohort of 38 patients. For predictive purposes we used a leave-one-out cross-validated (LOOCV) model with a positive predictive value (PPV) of 80%. Classifier optimisation with Random Forest identified FN1 and COL3A1 as the best predictors. Rebuilding the LOOCV regression model improved the classification performance with a PPV of 89.5% and a negative predictive value (NPV) of 73.7%. An independent cohort of 36 patients was used to validate the classifier performance, which had a PPV of 84.2% and an NPV of 70.6%. In a multivariate analysis the two-protein classifier proved to be the only independent predictor of response (HR=2.58; P=0.003). We also explored a pharmacogenomic approach to gather information about possible therapeutic strategies for non-responder patients. In conclusion, we developed a two-protein immunohistochemical classifier that performs well at predicting the absence of response to neoadjuvant treatment in rectal cancer.

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MicroRNA expression in preoperative chemoradiotherapy for rectal cancer (LARC)

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