Skip to content
#protein folding Open access

Comment on the article [Expression of miR-101-3p and its target ADAM15 gene in colorectal cancer patients]

Sep 2026 · Cukurova Medical Journal · 0 citations · 4 references
MicroRNA in disease regulation

Abstract

To the Editor,We read with interest the study titled "Expression of miR-101-3p and its target ADAM15 gene in colorectal cancer patients" published in the Çukurova Medical Journal . The authors' study is significant in that it draws attention to the potential relationship between miR-101-3p and ADAM15 in colorectal cancer and provides a basis for hypothesis generation. The topic is relevant, particularly given the increasing interest in miRNA-mediated regulatory networks in colorectal cancer. However, we would like to bring to constructive discussion certain aspects that warrant attention regarding the article's methodology, data presentation, and interpretation.The authors used β-actin as the reference gene for normalizing both miR-101-3p and ADAM15 mRNA expression. However, the use of protein-coding mRNAs like β-actin in miRNA quantification is methodologically controversial. This is because mature miRNAs and mRNAs differ significantly in size, stability, and cDNA synthesis efficiency. In the literature, U6 snRNA, RNU48, RNU6B or reference miRNAs showing stable expression are recommended for miRNA normalization2. ΔΔCt results based on a single and inappropriate reference gene can directly affect the direction and magnitude of expression changes. Additionally, the biological effect of ADAM15 occurs at the protein level. Increased mRNA levels alone do not prove a relationship with invasion, migration, shedding activity, or metastasis. We believe that ADAM15 protein levels should be confirmed by Western blot or immunohistochemistry3.Formalin-fixed paraffin-embedded (FFPE) samples pose significant technical limitations due to RNA cross-linking and fragmentation. The authors reported the (A260-A320)/(A280-A320) > 1.8 criterion but did not provide information on RNA integrity indicators (RIN, DV200). Although miRNAs are more resistant to fragmentation compared to mRNAs, for reliable quantification of ADAM15 mRNA, the DV200 value should have been reported4.The central hypothesis of the study is that miR-101-3p suppresses ADAM15 at the post-transcriptional level. However, the presented data consist solely of expression correlation in matched tumor/normal tissues. The authors themselves acknowledge this limitation in the discussion section. Common regulatory mechanisms, such as tumor stage, cellular composition, stromal contamination, hypoxia, inflammation, or epigenetic changes, may simultaneously cause low miR-101-3p levels and high ADAM15 expression.For the biomarker claim, the relationship of miR-101-3p and ADAM15 expressions with clinicopathological parameters such as stage, location, histological type or age should be examined, and survival or response to treatment data should be provided for prognostic prediction. The study's sample size is limited to n=30 and no power analysis is provided. This number is insufficient, especially for subgroup comparisons.In the results text, the expression "2.83-fold change, 183% increase" is used for the ADAM15 fold-change value. In contrast, the title of Figure 4 states "2.28-fold," while within the figure, the value 2.82 is visualized along with "282% increase." Providing three different values in three different places creates uncertainty for the reader.We hope that these constructive criticisms will contribute to the authors and to researchers who will work in similar fields in the future. We express our respect for the effort put in by the authors.

Read PDF

Similar papers

#computer vision Review Open access May 2015

A survey study on major technical barriers affecting the decision to adopt cloud services

The comparison of adopter and non-adopter sample reveals three potential adoption inhibitor, security, data privacy, and portability, which underlines the importance of the technical and security perspectives for research investigating the adoption of technology.

Nattakarn Phaphoom, Xiaofeng Wang, S. Samuel et al. · 111 citations · ⚡8
#computer vision Open access Feb 2018

Lean Internal Startups for Software Product Innovation in Large Companies: Enablers and Inhibitors

This study investigates how Lean internal startup facilitates software product innovation in large companies and identifies its enablers and inhibitors, and shows the potential of the method-in-action framework to investigate the Lean startup approach in non-startup context.

Henry Edison, Nina M. Smørsgård, Xiaofeng Wang et al. · 78 citations · ⚡6
#computer vision Book Open access Jul 2015

Understanding the affect of developers: theoretical background and guidelines for psychoempirical software engineering

This paper highlights the challenges to conduct proper affect-related studies with psychology, provides a comprehensive literature review in affect theory, and proposes guidelines for conducting psychoempirical software engineering.

D. Graziotin, Xiaofeng Wang, P. Abrahamsson · 56 citations · ⚡4
#machine learning Open access May 2017

What Influences the Speed of Prototyping? An Empirical Investigation of Twenty Software Startups

This study conducts a multiple case study on twenty European software startups and proposes a prototype-centric learning model in early stage software startups, and identifies factors that occur as barriers but also facilitators for prototyping in earlystage software startups.

Anh Nguyen-Duc, Xiaofeng Wang, P. Abrahamsson · 44 citations · ⚡5
#protein folding Open access Sep 2026

Programmable design of functional proteins from natural language

Pinal, a 16-billion-parameter foundation model that produces protein candidates from natural-language functional descriptions, supports natural language as a high-level interface for candidate generation in protein design, enabling programmable exploration with reduced reliance on manually specified structural or seque...

Fengyuan Dai, Shiyang You, Yudian Zhu et al. · 31 citations · ⚡3

Related blog posts

Google DeepMind Blog Sep 30, 2026

Introducing SynthID Bio

Proof of concept for watermarking AI-generated proteins while preserving biological function.

MIT News · Artificial Intelligence Aug 27, 2026

Looking beyond natural sequences

A new machine-learning framework aims to improve the success rate of computational protein design while moving away from results that reproduce sequences found in nature.

We use cookies to run the site and, with your consent, for analytics and to show ads. See our Cookie Policy.