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We were at EuPA 2022

P169 – Activation of the prothrombin and complement systems appears to be involved at a different level in the progression of colorectal cancer

Question

Colorectal cancer (CRC) is one of the most common cancers. Early detection of CRC remains a challenge and the identification of new biomarkers represents a relevant target. Several authors highlighted that serum peptidomic patterns may be correlated with events occurring in all districts of the organism. Mass spectrometry is well suited for the detection of low molecular weight proteins that might well represent a dynamic reflection of tissue function. The aim of the present work is the determination of a serum peptidome signature able to help in the CRC diagnosis and prognosis.

Methods

Blood samples from 180 patients with CRC and 70 healthy volunteers were collected. The extraction of the low molecular weight fraction of serum proteome has been performed using Dynabeads RPC 18 beads. MALDI/TOF spectra were acquired in a range from 800 to 3000 m/z. All serum samples were tested for their integrity by means of Seradeg (1), a publicly available web tool aimed at assessing the quality of sera. According to this analysis, only a subset of 170 samples was used in the following comparison. The final set included 170 samples, of which 92 patients had been diagnosed with metastatic CRC, 78 patients had been diagnosed with non-metastatic CRC, and 20 were healthy volunteers. The lists of significant peaks were analysed by means of Geena 2 (2), a publicly available web tool for pre-processing of MALDI/TOF. The output generated by Geena 2 was then analysed by means of SAMR (3), in order to identify signals significantly different in the main data sets, i.e. healthy volunteers, metastatic CRC and non-metastatic CRC. The findings were also validated by a bootstrap resampling procedure. Multiple regression models were used to validate the findings of the SAM analysis taking into account the differences in age and gender between patients and controls.

Results

The SAMR analysis put in evidence a peptide signature able to distinguish between healthy volunteers and CRC patients, which includes the m/z 1561.72 (human prothrombin P00734, fragment “TATSEYQTFFNPR”) and m/z 2021.08 (C3 complement P01024, C3f complement fragment “SSKITHRIHWESASLLR”). In particular, our results show that the intensity of these two signals was higher in the serum samples from CRC patients than in those from healthy controls. Interestingly, while the difference for m/z 2021.08 signal was only significant between healthy volunteers and metastatic CRC, the difference for m/z 1561.72 was significant between healthy volunteers and nonmetastatic CRC too.

Conclusions

Our results showed that prothrombin and complement system activation are involved in CRC progression. However, they may provide a novel approach for a better classification of CRC patients only after a validation on an independent larger set of sample.

References

  1. Romano P et al., Journal of Proteomics 2018, 173, 99–106.
  2. Romano P et al., BMC Bioinformatics 2016, 17(Suppl 4), 61.
  3. Samr: https://github.com/MikeJSeo/SAM).

New current research project approved

Castration-resistant prostate cancer (CRPC): use of cell models to the study and testing of new therapies approches

Results of last three years of the “Ricerca Corrente” project lead by Dr Paola Barboro have been presented as a poster at the 1st HSM Retreat.

Barboro P.
Castration-resistant prostate cancer (CRPC): use of cell models to the study and testing of new therapies approches
First HSM Retreat, Genoa, November 4-5, 2021. P10.

Molecular modeling for the design and synthesis of new formulations of pharmacological interest and their delivery

A poster summarizing results of the research activity carried out during last three years by the Unit has been presented at the 1st HSM Retreat.

Aprile A, Bachetti T, Iervasi E, Ponassi M, Profumo A, Rocco M, Romano P, Rosano C.
Molecular modeling for the design and synthesis of new formulations of pharmacological interest and their delivery.
First HSM Retreat, Genoa, November 4-5, 2021. P50.

Structural, differential and functional metabolomics and proteomics studies in oncology

A poster summarizing results of the research activity carried out during last three years by the Unit has been presented at the 1st HSM Retreat.

Aprile A, Bachetti T, Iervasi E, Ponassi M, Profumo A, Rocco M, Romano P, Rosano C.
Structural, differential and functional metabolomics and proteomics studies in oncology
First HSM Retreat, Genoa, November 4-5, 2021. P46.

GeenaR: a web tool for reproducible MALDI-TOF analysis

A new research article from the Unit is out.
Frontiers in Genetics have published the manuscript “GeenaR: a web tool for reproducible MALDI-TOF analysis” by Eugenio Del Prete, Angelo Facchiano, Aldo Profumo, Claudia Angelini and Paolo Romano.
doi: 10.3389/fgene.2021.635814.

Abstract
Mass spectrometry is a widely applied technology with a strong impact in the proteomics field. MALDI-TOF is a combined technology in mass spectrometry with many applications in characterizing biological samples from different sources, such as the identification of cancer biomarkers, the detection of food frauds, the identification of doping substances in athletes’ fluids, and so on. The massive quantity of data, in the form of mass spectra, are often biased and altered by different sources of noise. Therefore, extracting the most relevant features that characterize the samples is often challenging and requires combining several computational methods.
Here, we present GeenaR, a novel web tool that provides a complete workflow for pre-processing, analyzing, visualizing, and comparing MALDI-TOF mass spectra. GeenaR is user-friendly, provides many different functionalities for the analysis of the mass spectra, and supports reproducible research since it produces a human-readable report that contains function parameters, results, and the code used for processing the mass spectra.
First, we illustrate the features available in GeenaR. Then, we describe its internal structure. Finally, we prove its capabilities in analyzing oncological datasets by presenting two case studies related to ovarian cancer and colorectal cancer.
GeenaR is available at http://proteomics.hsanmartino.it/geenar/.

Cite the manuscript as follows:
Del Prete E, Facchiano A, Profumo A, Angelini C, Romano P. GeenaR: a web tool for reproducible MALDI-TOF analysis. Front. Genet. 29 March 2021. 12:635814. doi: 10.3389/fgene.2021.635814