Locally advanced rectal cancer transcriptomic-based secretome analysis reveals novel biomarkers useful to identify patients according to neoadjuvant chemoradiotherapy response

Canto, Luísa Matos do; Cury, Sarah Santiloni; Barros-Filho, Mateus Camargo; Kupper, Bruna Elisa Catin; Begnami, Maria D.; Scapulatempo‐Neto, Cristovam; Carvalho, Robson Francisco; Marchi, Fábio Albuquerque; Olsen, Dorte Aalund; Madsen, Jonna Skov; Havelund, Birgitte Mayland; Aguiar, Samuel; Rogatto, Sílvia Regina

doi:10.1038/s41598-019-45151-w

Cited by 14 publications

(15 citation statements)

References 68 publications

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“…Contrarily, we identified DM probes in CpGs within the MGMT gene body in pIR cases. Although alteration in gene expression due to DM regions in gene bodies has been previously reported [44,45], we found no correlation of the abovementioned DM probes and MGMT expression, evaluated in our previous transcriptomic data performed in the same group of cases (GSE123390) [36].…”

Section: Discussioncontrasting

confidence: 85%

“…Targeted next-generation sequencing data of a panel with 105 cancer-related genes from 30 of the 32 LARC cases were retrieved from our previous study [ 35 ] (deposited at Sequence Read Archive–SRA: PRJNA535396) to assess variants in key CRC-related genes. To evaluate the correlation between CpG-specific methylation levels and gene expression, we used the matched microarray-based transcriptomic data from 27 of 32 LARC cases previously reported by our group (GSE123390) [ 36 ]. To further explore these correlations in an independent set of LARC cases, we retrieved the matching methylation (Infinium HumanMethylation450k BeadChip) and transcriptomic (RNA-Seq) data publicly available from 33 LARC cases from TCGA-READ study using the Wanderer interactive online tool ( ) [ 71 ].…”

Section: Methodsmentioning

confidence: 99%

“…Combining DNA methylation and gene expression can bring insights to explain the predictive impact on the response to therapy of LARC patients. We integrated the DNA methylation used in the discovery phase of our study with our previous study of gene expression levels (GSE123390) of 27 LARC [36]. The CpG-A, CpG-B, and CpG-C are associated with OBSL1 (Obscurin Like Cytoskeletal Adaptor 1), GPR1 (G Protein-Coupled Receptor 1), and INSIG1 (Insulin-induced gene 1) loci, respectively.…”

Section: Prediction Of the Impact Of Dna Methylation Changes Of The Cmentioning

confidence: 99%

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Comprehensive Analysis of DNA Methylation and Prediction of Response to NeoadjuvantTherapy in Locally Advanced Rectal Cancer

Canto

Barros-Filho

Rainho

et al. 2020

Cancers

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The treatment for locally advanced rectal carcinomas (LARC) is based on neoadjuvant chemoradiotherapy (nCRT) and surgery, which results in pathological complete response (pCR) in up to 30% of patients. Since epigenetic changes may influence response to therapy, we aimed to identify DNA methylation markers predictive of pCR in LARC patients treated with nCRT. We used high-throughput DNA methylation analysis of 32 treatment-naïve LARC biopsies and five normal rectal tissues to explore the predictive value of differentially methylated (DM) CpGs. External validation was carried out with The Cancer Genome Atlas-Rectal Adenocarcinoma (TCGA-READ 99 cases). A classifier based on three-CpGs DM (linked to OBSL1, GPR1, and INSIG1 genes) was able to discriminate pCR from incomplete responders with high sensitivity and specificity. The methylation levels of the selected CpGs confirmed the predictive value of our classifier in 77 LARCs evaluated by bisulfite pyrosequencing. Evaluation of external datasets (TCGA-READ, GSE81006, GSE75546, and GSE39958) reproduced our results. As the three CpGs were mapped near to regulatory elements, we performed an integrative analysis in regions associated with predicted cis-regulatory elements. A positive and inverse correlation between DNA methylation and gene expression was found in two CpGs. We propose a novel predictive tool based on three CpGs potentially useful for pretreatment screening of LARC patients and guide the selection of treatment modality.

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Section: Discussioncontrasting

confidence: 85%

Section: Methodsmentioning

confidence: 99%

Section: Prediction Of the Impact Of Dna Methylation Changes Of The Cmentioning

confidence: 99%

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Comprehensive Analysis of DNA Methylation and Prediction of Response to NeoadjuvantTherapy in Locally Advanced Rectal Cancer

Canto

Barros-Filho

Rainho

et al. 2020

Cancers

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“…Similarly to other studies, the accuracy of the prediction improved when a qualitative MRI assessment is added to a quantitative radiomic-based analysis 21,51 . In this way we are confident that the development of other "omics" disciplines may further improve the overall accuracy of the treatment response prediction 63,64 . Our study has some limitation.…”

Section: Discussionmentioning

confidence: 87%

MRI-based clinical-radiomics model predicts tumor response before treatment in locally advanced rectal cancer

Pizzi

Chiarelli

Chiacchiaretta

et al. 2021

Sci Rep

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Neoadjuvant chemo-radiotherapy (CRT) followed by total mesorectal excision (TME) represents the standard treatment for patients with locally advanced (≥ T3 or N+) rectal cancer (LARC). Approximately 15% of patients with LARC shows a complete response after CRT. The use of pre-treatment MRI as predictive biomarker could help to increase the chance of organ preservation by tailoring the neoadjuvant treatment. We present a novel machine learning model combining pre-treatment MRI-based clinical and radiomic features for the early prediction of treatment response in LARC patients. MRI scans (3.0 T, T2-weighted) of 72 patients with LARC were included. Two readers independently segmented each tumor. Radiomic features were extracted from both the “tumor core” (TC) and the “tumor border” (TB). Partial least square (PLS) regression was used as the multivariate, machine learning, algorithm of choice and leave-one-out nested cross-validation was used to optimize hyperparameters of the PLS. The MRI-Based “clinical-radiomic” machine learning model properly predicted the treatment response (AUC = 0.793, p = 5.6 × 10–5). Importantly, the prediction improved when combining MRI-based clinical features and radiomic features, the latter extracted from both TC and TB. Prospective validation studies in randomized clinical trials are warranted to better define the role of radiomics in the development of rectal cancer precision medicine.

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“…More recently, novel biomarkers useful to identify patients according to nCRT response have been revealed through transcriptomic-based secretome approach. Particularly, 17 potentially secreted candidates were identified as over-expressed in LARC and associated with nCRT response [ 116 ].…”

Section: Circulating Biomarkers To Predict Response To Ncrt In Larmentioning

confidence: 99%

The Role of Micro-RNAs and Circulating Tumor Markers as Predictors of Response to Neoadjuvant Therapy in Locally Advanced Rectal Cancer

Palma

Luglio

Tropeano

et al. 2020

IJMS

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The response to neoadjuvant chemoradiation (nCRT) is a critical step in the management of locally advanced rectal cancer (LARC) patients. Only a minority of LARC patients responds completely to neoadjuvant treatments, thus avoiding invasive radical surgical resection. Moreover, toxic side effects can adversely affect patients’ survival. The difficulty in separating in advances responder from non-responder patients affected by LARC highlights the need for valid biomarkers that guide clinical decision-making. In this context, microRNAs (miRNAs) seem to be promising candidates for predicting LARC prognosis and/or therapy response, particularly due to their stability, facile detection, and disease-specific expression in human tissues, blood, serum, or urine. Although a considerable number of studies involving potential miRNA predictors to nCRT have been conducted over the years, to date, the identification of the perfect miRNA signatures or single miRNA, as well as their use in the clinical practice, is still representing a challenge for the management of LARC patients. In this review, we will first introduce LARC and its difficult management. Then, we will trace the scientific history and the key obstacles for the identification of specific miRNAs that predict responsiveness to nCRT. There is a high potential to identify non-invasive biomarkers that circulate in the human bloodstream and that might indicate the LARC patients who benefit from the watch-and-wait approach. For this, we will critically evaluate recent advances dealing with cell-free nucleic acids including miRNAs and circulating tumor cells as prognostic or predictive biomarkers.

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Locally advanced rectal cancer transcriptomic-based secretome analysis reveals novel biomarkers useful to identify patients according to neoadjuvant chemoradiotherapy response

Cited by 14 publications

References 68 publications

Comprehensive Analysis of DNA Methylation and Prediction of Response to NeoadjuvantTherapy in Locally Advanced Rectal Cancer

Comprehensive Analysis of DNA Methylation and Prediction of Response to NeoadjuvantTherapy in Locally Advanced Rectal Cancer

MRI-based clinical-radiomics model predicts tumor response before treatment in locally advanced rectal cancer

The Role of Micro-RNAs and Circulating Tumor Markers as Predictors of Response to Neoadjuvant Therapy in Locally Advanced Rectal Cancer

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