DNA methylation-based classifier to predict pathological complete response to neoadjuvant chemoradiotherapy in locally advanced rectal carcinomas.
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PROVIDER: PRJNA548688 | ENA |
REPOSITORIES: ENA
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Project description:Locally advanced rectal cancer (LARC) patients have been treated with a pre-operative multimodal regimen based on 5-fluorouracil and radiotherapy (nCRT) followed by surgery. Patients that achieve pathological complete response (pCR) present better overall survival and lower rates of recurrence. Substantial evidence indicate that these patients could be spared of surgery, while near 70% of cases present incomplete response (pIR), varying from partial response to stable-disease/progression. Markers capable of distinguishing pIR from pCR have the potential to address alternative treatment strategies. Herein, we evaluated the ability of predicting response to nCRT by DNA methylation analysis in pre-treatment biopsies of LARC.
2021-06-08 | GSE132668 | GEO
Project description:Most patients with locally advanced rectal cancer (LARC) present incomplete pathological response (pIR) to neoadjuvant chemoradiotherapy (nCRT). Despite the efforts to predict treatment response using tumor-molecular features, as differentially expressed genes, no molecule has proved to be a strong biomarker. The tumor secretome analysis is a promising strategy for biomarkers identification, which can be assessed using transcriptomic data. Here, we performed transcriptomic-based secretome analysis to select potentially secreted proteins using an in silico approach. The tumor expression profile of 28 LARC biopsies carefully selected and collected before nCRT was compared with normal rectal tissues (NT). The expression profile showed no significant differences between cases with complete (pCR) and incomplete response to nCRT. Genes with increased expression (pCR = 106 and pIR = 357) were used for secretome analysis based on public databases (Vesiclepedia, Human Cancer Secretome Database and Plasma and Proteome Database). Seventeen potentially secreted candidates (pCR=1, pIR=13 and 3 in both groups) were further investigated in two independent datasets (TCGA and GSE68204) confirming their over-expression in LARC. The potential secreted biomarkers were also confirmed as associated with the nCRT response (GSE68204). These putative proteins are candidates to be assessed in liquid biopsies aiming a personalized treatment in LARC patients.
2019-07-01 | GSE123390 | GEO
Project description:Locally advanced rectal cancer transcriptomic-based secretome analysis according to neoadjuvant chemoradiotherapy response
| PRJNA510936 | ENA
Project description:To measure global gene expression in primary locally advanced rectal cancer patients who have undergone CRT and screen valuable biomarkers to predict the effects of CRT.Samples fromprimary locally advanced rectal cancer patients were collected. The effects of chemoradiotherapy were evaluated.
2021-06-04 | GSE145037 | GEO
Project description:Background: Neoadjuvant chemoradiotherapy (NCRT) is the treatment of choice in advanced rectal cancer, even though there are many patients who will not benefit from it. There are still no effective methods for predicting which patients will respond or not. The present study aimed to define the genomic profile of rectal tumors and to identify alterations that are predictive of response in order to optimize therapeutic strategies. Methods: Forty-eight candidates for NCRT were recruited and their pretherapy biopsies analyzed by array Comparative Genomic Hybridization (aCGH). Pathologic response was evaluated by tumor regression grade (TRG).Results: Both Smoothing and Hidden Markov Model (HMM) approaches identified similar alterations, with a prevalence of DNA gains. Non responsive patients had a different alteration profile from responsive ones, with a higher number of genome changes mainly located on 2q21, 7q21, 7q36, 13q12, 13q32-34, 16p13, 17p12 chromosomal regions. Conclusion: This exploratory study suggests that an in depth characterization of chromosomal alterations by aCGH would provide useful predictive information about response to NCRT and help to optimize therapy in rectal cancer patients.
2011-11-17 | GSE25885 | GEO
Project description:The treatment strategy of rectal cancer has substantially changed in recent decades. Historically postoperative chemoradiotherapy (CRT) was considered to be the first-line therapy for stage II and III rectal cancers. However, the preoperative CRT is now considered to be the optimal therapy regimen for locally advanced rectal ancer due to its improved local control, reduced toxicity, and increased rate of sphincter preservation. Our study established a clinically practical multi-class prediction model by adopting a novel strategy that applies two separate prediction models (MI and TO predictor) sequentially to a patient to predict the response. For promising clinical practice, we validated our model in a published dataset, which is completely independent dataset from ours. This study suggests a clinically plausible prediction model that correctly infers the preoperative CRT response of patients with high accuracy based on 163 gene signatures we identified. Total RNAs were isolated from primary rectal tumor tissues of 69 patients who underwent chemoradiation therapy (CRT). These patients are classified into four different CRT responses: minimal response (MI), moderate response (MO), near total response (NT) and total response (TO). All the RNAs were subjected to microarray analysis using Affymetrix GenChip arrays.
2013-05-14 | E-GEOD-46862 | biostudies-arrayexpress
Project description:The treatment strategy of rectal cancer has substantially changed in recent decades. Historically postoperative chemoradiotherapy (CRT) was considered to be the first-line therapy for stage II and III rectal cancers. However, the preoperative CRT is now considered to be the optimal therapy regimen for locally advanced rectal ancer due to its improved local control, reduced toxicity, and increased rate of sphincter preservation. Our study established a clinically practical multi-class prediction model by adopting a novel strategy that applies two separate prediction models (MI and TO predictor) sequentially to a patient to predict the response. For promising clinical practice, we validated our model in a published dataset, which is completely independent dataset from ours. This study suggests a clinically plausible prediction model that correctly infers the preoperative CRT response of patients with high accuracy based on 163 gene signatures we identified.
2013-05-14 | GSE46862 | GEO
Project description:Unique sub-clones within rectal tumors may harbor mutations which contribute to inter-patient variation in response to neoadjuvant chemoradiotherapy (nCRT). Analysis of the influence of nCRT on the extent and nature of intra-tumoral genetic heterogeneity in rectal cancer may provide insights into mechanisms of resistance. Ten locally advanced rectal cancer patients underwent pre-treatment biopsies. At the time of surgery, tissue from the treated tumor was obtained and analyzed. Pre- and post-treatment specimens were subjected to whole exome and confirmatory deep sequencing for somatic mutations. Copy number variation was assessed using OncoScan SNP arrays. In total, data from 32 pre/post-treatment samples are provided. The provided data include the pre/post tumor samples and the Affymetrix OncoScan SNP arrays.
2019-09-05 | GSE136872 | GEO
Project description:Background: Neoadjuvant chemoradiotherapy (NCRT) is the treatment of choice in advanced rectal cancer, even though there are many patients who will not benefit from it. There are still no effective methods for predicting which patients will respond or not. The present study aimed to define the genomic profile of rectal tumors and to identify alterations that are predictive of response in order to optimize therapeutic strategies. Methods: Forty-eight candidates for NCRT were recruited and their pretherapy biopsies analyzed by array Comparative Genomic Hybridization (aCGH). Pathologic response was evaluated by tumor regression grade (TRG).Results: Both Smoothing and Hidden Markov Model (HMM) approaches identified similar alterations, with a prevalence of DNA gains. Non responsive patients had a different alteration profile from responsive ones, with a higher number of genome changes mainly located on 2q21, 7q21, 7q36, 13q12, 13q32-34, 16p13, 17p12 chromosomal regions. Conclusion: This exploratory study suggests that an in depth characterization of chromosomal alterations by aCGH would provide useful predictive information about response to NCRT and help to optimize therapy in rectal cancer patients. 48 samples included in the study were analyzed on whole genome BAC arrays with the aim to characterize genomic alterations and correlate them with the tumor response to therapy. The case series was composed by 15%,81% and 4% of uT2, uT3 and uT4 tumors, respectively. At the diagnosis 56% of patients had uN0 tumors and 44% uN+. 30%,13%, 23% and 34% of patients reached/mantained respectively ypT0, ypT1, ypT2 and ypT3. With regard to response to NCRT, according to TRG criteria proposed by Dworak, two group were defined: non responders (TRG0-2= 56%) and responders (TRG3-4=44%). Clinical and pathological parameters: uT: pre-therapy stage determined by ultrasounds techniques uN: pre-therapy lymph node status determined by ultrasounds techniques ypT: pathologic stage after a neoadjuvant treatment ypN: pathologic lymph node status after a neoadjuvant treatment
2011-11-17 | E-GEOD-25885 | biostudies-arrayexpress
Project description:Locally advanced rectal cancer (LARC) exhibits heterogeneous responses to neoadjuvant chemoradiotherapy (nCRT), patients resistant to nCRT failing to benefit from to nCRT. The aim of this pilot study is to identify proteins associated with LARC nCRT-resistance. This pilot study retrospectively enrolled 4 representative nCRT-resistant (stable disease/progressive disease) and 4 nCRT-sensitive (complete response/partial response) patients, of which a total of 15 formalin-fixed paraffin-embedded tumor tissues (before and after nCRT) were subjected to data-independent acquisition mass spectrometry for proteomic analysis. Spectronaut software was employed for protein identification and quantification. Principal component analysis (PCA) was used to visualize intergroup differences in detected proteins. Differently abundant proteins in resistant patients (fold change ≥ 1.2 or ≤ 0.83 compare to sensitive patients) were selected for analysis using hierarchical clustering, cluster of orthologous groups, subcellular location, gene ontology, and pathway enrichment assay. A total of 39052 peptides and 6006 proteins were identified. PCA showed PCA clear separation among four groups: pre-treatment sensitive (B_S), pre-treatment resistant (B_R), post-treatment sensitive (P_S), and post-treatment resistant (P_R). Intergroup comparisons revealed before nCRT, 133 proteins were upregulated in the resistant group compared to the sensitive group, mainly localized in cytoplasm (33.08%), secreted (24.81%), and nucleus (24.06%), with functions enriched in cell junctions and metabolic related pathways. Post nCRT, 290 proteins were upregulated in the resistant group compared to the sensitive group, mainly localized in the nucleus (36.55%) and cytoplasm (23.10%), with functions enriched in replication, transcription, translation, and metabolic pathways. This study characterized DAP signatures of LARC with nCRT resistance, specific DAPs in resistant tumor provide references for mechanistic studies on treatment resistance, could be potential biomarker for response and therapeutic targets after further validation in larger cohorts.
2025-10-17 | PXD069647 |