Summary of Study ST003045
This data is available at the NIH Common Fund's National Metabolomics Data Repository (NMDR) website, the Metabolomics Workbench, https://www.metabolomicsworkbench.org, where it has been assigned Project ID PR001895. The data can be accessed directly via it's Project DOI: 10.21228/M8S14W This work is supported by NIH grant, U2C- DK119886.
See: https://www.metabolomicsworkbench.org/about/howtocite.php
This study contains a large results data set and is not available in the mwTab file. It is only available for download via FTP as data file(s) here.
| Study ID | ST003045 |
| Study Title | Proteomic and metabolomic signatures of rectal tumor discriminate patients with different responses to preoperative radiotherapy |
| Study Summary | Background: Neoadjuvant radiotherapy (neo-RT) is widely used in locally advanced rectal cancer (LARC) as a component of radical treatment. Despite the advantages of neo-RT, which typically improves outcomes in LARC patients, the lack of reliable biomarkers that predict response and monitor the efficacy of therapy, can result in the application of unnecessary aggressive therapy affecting patients’ quality of life. Hence, the search for molecular biomarkers for assessing the radio responsiveness of this cancer represents a relevant issue. Methods: Here, we combined proteomic and metabolomic approaches to identify molecular signatures, which could discriminate LARC tumors with good and poor responses to neo-RT. Results: The integration of data on differentially accumulated proteins and metabolites made it possible to identify disrupted metabolic pathways and signaling processes connected with response to irradiation, including ketone bodies synthesis and degradation, purine metabolism, energy metabolism, degradation of fatty acid, amino acid metabolism, and focal adhesion. Moreover, we proposed multi-component panels of proteins and metabolites which could serve as a solid base to develop biomarkers for monitoring and predicting the efficacy of preoperative RT in rectal cancer patients. Conclusions: We proved that an integrated multi-omic approach presents a valid look at the analysis of the global response to cancer treatment from the perspective of metabolomic reprogramming. |
| Institute | Institute of Bioorganic Chemistry Polish Academy of Sciences |
| Last Name | Wojakowska |
| First Name | Anna |
| Address | Noskowskiego 12/14, Poznan, Greater Poland, 61-704, Poland |
| astasz@ibch.poznan.pl | |
| Phone | +48616653051 |
| Submit Date | 2024-01-17 |
| Raw Data Available | Yes |
| Raw Data File Type(s) | cdf |
| Analysis Type Detail | GC-MS |
| Release Date | 2024-02-08 |
| Release Version | 1 |
Select appropriate tab below to view additional metadata details:
Project:
| Project ID: | PR001895 |
| Project DOI: | doi: 10.21228/M8S14W |
| Project Title: | Proteomic and metabolomic signatures of rectal tumor discriminate patients with different responses to preoperative radiotherapy |
| Project Summary: | Background: Neoadjuvant radiotherapy (neo-RT) is widely used in locally advanced rectal cancer (LARC) as a component of radical treatment. Despite the advantages of neo-RT, which typically improves outcomes in LARC patients, the lack of reliable biomarkers that predict response and monitor the efficacy of therapy, can result in the application of unnecessary aggressive therapy affecting patients’ quality of life. Hence, the search for molecular biomarkers for assessing the radio responsiveness of this cancer represents a relevant issue. Methods: Here, we combined proteomic and metabolomic approaches to identify molecular signatures, which could discriminate LARC tumors with good and poor responses to neo-RT. Results: The integration of data on differentially accumulated proteins and metabolites made it possible to identify disrupted metabolic pathways and signaling processes connected with response to irradiation, including ketone bodies synthesis and degradation, purine metabolism, energy metabolism, degradation of fatty acid, amino acid metabolism, and focal adhesion. Moreover, we proposed multi-component panels of proteins and metabolites which could serve as a solid base to develop biomarkers for monitoring and predicting the efficacy of preoperative RT in rectal cancer patients. Conclusions: We proved that an integrated multi-omic approach presents a valid look at the analysis of the global response to cancer treatment from the perspective of metabolomic reprogramming. |
| Institute: | Institute of Bioorganic Chemistry Polish Academy of Sciences |
| Last Name: | Wojakowska |
| First Name: | Anna |
| Address: | Noskowskiego 12/14, Poznan, Greater Poland, 61-704, Poland |
| Email: | astasz@ibch.poznan.pl |
| Phone: | +48616653051 |
Subject:
| Subject ID: | SU003160 |
| Subject Type: | Human |
| Subject Species: | Homo sapiens |
| Taxonomy ID: | 9606 |
| Gender: | Male and female |
Factors:
Subject type: Human; Subject species: Homo sapiens (Factor headings shown in green)
| mb_sample_id | local_sample_id | Experimental factor |
|---|---|---|
| SA330493 | GR_296 | GR |
| SA330494 | GR_282 | GR |
| SA330495 | GR_186 | GR |
| SA330496 | GR_384 | GR |
| SA330497 | GR_386 | GR |
| SA330498 | GR_415 | GR |
| SA330499 | GR_406 | GR |
| SA330500 | GR_153 | GR |
| SA330501 | GR_63 | GR |
| SA330502 | GR_50 | GR |
| SA330503 | PR_12 | PR |
| SA330504 | PR_401 | PR |
| SA330505 | PR_398 | PR |
| SA330506 | PR_92 | PR |
| SA330507 | PR_100 | PR |
| SA330508 | PR_150 | PR |
| SA330509 | PR_148 | PR |
| SA330510 | PR_260 | PR |
| Showing results 1 to 18 of 18 |
Collection:
| Collection ID: | CO003153 |
| Collection Summary: | Tissue samples were taken from 24 LARC patients diagnosed with adenocarcinoma and treated at Maria Skłodowska-Curie National Research Institute of Oncology, Gliwice Branch. All patients were given neo-RT in a total dose of 39-54Gy. Tissue samples were collected between 2012 and 2014, directly during a standard surgical treatment; resected tissue samples were immediately frozen and kept at -80 °C until analysis performed in 2020. The histology of three tissue slices (from the edges and center of the studied tissue sample) was assessed by an experienced pathologist for the percentage of tumor cells in each case. TRG assessed routinely in resected tumors reflected the area of residual tumor cells compared to the fibrotic area: TRG0 - complete response/no residual tumor, TRG1 - 10% of residual tumor, TRG2 - 10-50% of residual tumor, and TRG3 - >50% of residual tumor. Depending on the response to the treatment and the presence of tumor cells, collected samples were classified into two groups: good responders (GR) – 12 patients with RT-sensitive tumors (TRG 0-1), and poor responders (PR) - 12 patients with RT-resistant tumors (TRG 2-3). |
| Sample Type: | Rectum |
Treatment:
| Treatment ID: | TR003169 |
| Treatment Summary: | All patients were given neo-RT in a total dose of 39-54Gy. Tissue samples were collected between 2012 and 2014, directly during a standard surgical treatment; resected tissue samples were immediately frozen and kept at -80 °C until analysis performed in 2020. The histology of three tissue slices (from the edges and center of the studied tissue sample) was assessed by an experienced pathologist for the percentage of tumor cells in each case. TRG assessed routinely in resected tumors reflected the area of residual tumor cells compared to the fibrotic area: TRG0 - complete response/no residual tumor, TRG1 - 10% of residual tumor, TRG2 - 10-50% of residual tumor, and TRG3 - >50% of residual tumor. Depending on the response to the treatment and the presence of tumor cells, collected samples were classified into two groups: good responders (GR) – 12 patients with RT-sensitive tumors (TRG 0-1), and poor responders (PR) - 12 patients with RT-resistant tumors (TRG 2-3). |
Sample Preparation:
| Sampleprep ID: | SP003166 |
| Sampleprep Summary: | 50 mg of pulverized tissue was extracted using 200 ul each of hexane, chloroform, methylene chloride, and methanol. The mixture was sonicated for 10 minutes each time after adding organic solvent, then centrifuged for 10 min at 11,000 x g at 4°C, and dried in a vacuum centrifuge. The dried extract was then subjected to derivatization by adding 40 μl of methoxyamine hydrochloride in pyridine (20 mg/ml) and incubated for 1.5h at 37 °C. Next, in the second derivatization step, 90 μl of N-Trimethylsilyl-N-methyl trifluoroacetamide was added, and samples were incubated at 37 °C for another 30 min. After derivatization, samples were immediately subjected to a GC/MS analysis. |
Combined analysis:
| Analysis ID | AN004995 |
|---|---|
| Analysis type | MS |
| Chromatography type | GC |
| Chromatography system | Thermo Trace 1310 |
| Column | Agilent DB5-MS (30m x 0.25mm, 0.25um) |
| MS Type | EI |
| MS instrument type | GC QQQ |
| MS instrument name | Thermo TSQ8000 |
| Ion Mode | POSITIVE |
| Units | normalized intensity |
Chromatography:
| Chromatography ID: | CH003774 |
| Chromatography Summary: | The GC-MS system (TRACE 1310 GC oven with TSQ8000 triple quad MS from Thermo Scientific, USA) with a DB-5MS column (30 m 0.25 mm 0.25 m) (J & W Scientific, Agilent Technologies, Palo Alto, California, USA) was used to separate and analyze metabolites. The following conditions were maintained for the gradient during chromatographic separation: 2 minutes at 70°C, followed by 10 minutes at 300°C, at 300°C. The source temperature was set to 250°C, the column interface was maintained at 250°C, and the PTV injector was used to inject the sample with a temperature gradient from 40 to 250°C. |
| Instrument Name: | Thermo Trace 1310 |
| Column Name: | Agilent DB5-MS (30m x 0.25mm, 0.25um) |
| Column Temperature: | 250 |
| Flow Gradient: | - |
| Flow Rate: | 1.2 ml/min |
| Solvent A: | - |
| Solvent B: | - |
| Chromatography Type: | GC |
MS:
| MS ID: | MS004735 |
| Analysis ID: | AN004995 |
| Instrument Name: | Thermo TSQ8000 |
| Instrument Type: | GC QQQ |
| MS Type: | EI |
| MS Comments: | The electron ionization energy of the ion source, which operated in the range of 50-850 m/z, was set at 70 eV. The mixture of retention indexes (RI) containing alkanes was run before relevant analyses. Raw data files were analyzed using MSDial software (v. 4.92). The correction against the alkane series mixture (C-10-36) was implemented directly in MS Dial to generate the RI for each compound. The 28,220 records in the MSP database from the CompMS site were used to identify small molecules. Metabolite was considered as identified if the similarity index (SI) was above 80%. The following analyses did not include the identified artifacts (alkanes, column bleed, plasticizers, MSTFA, and reagents). Results that had been normalized (by applying the TIC approach) were exported and used in statistical analyses |
| Ion Mode: | POSITIVE |
