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Cancers
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Predictive Biomarkers for Colorectal Cancer
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Predictive Biomarkers for Colorectal Cancer

A special issue of Cancers (ISSN 2072-6694). This special issue belongs to the section "Cancer Biomarkers".

Deadline for manuscript submissions: 21 June 2024 | Viewed by 5200

Special Issue Editor

Dr. Mitsukuni Suenaga

E-Mail Website
Guest Editor
Department of Clinical Oncology, Graduate School of Medical and Dental Sciences, Tokyo Medical and Dental University (TMDU), 1-5-45 Yushima, Bunkyo-Ku, Tokyo 113-8510, Japan
Interests: gastrointestinal cancer; medical oncology; tumor biology; translational research

Special Issue Information

Dear Colleagues,

An ideal biomarker can help provide optimal treatment by predicting the efficacy and safety of chemotherapeutic treatments, including biologics and immune checkpoint inhibitors. Although many biomarker studies have been reported to date, few validated markers have been identified. In recent years, genetic testing for RAS, BRAF, and MSI has led to the development of individualized treatment for colorectal cancer, and research using new diagnostic techniques is actively being conducted worldwide.

This Special Issue includes RNA and miRNA expression analysis, determination of methylation status, DNA and RNA sequencing, RNA quantification, SNP genotyping, genetic analysis of circulating tumor DNA, and analysis of plasma cytokine levels. Finally, we aim to highlight potential predictive markers for colorectal cancer patients receiving anticancer therapy.

Dr. Mitsukuni Suenaga
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Cancers is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2900 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • colorectal cancer
  • biomarker
  • chemotherapy
  • precision medicine
  • genetic analysis

Published Papers (5 papers)

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Research

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20 pages, 4440 KiB  
Article
Expression of Mitochondrial Long Non-Coding RNAs, MDL1 and MDL1AS, Are Good Prognostic and/or Diagnostic Biomarkers for Several Cancers, Including Colorectal Cancer
by Pablo Garrido, Adrián Casas-Benito, Ignacio M. Larrayoz, Judit Narro-Íñiguez, Susana Rubio-Mediavilla, Enrique Zozaya, Alfonso Martín-Carnicero and Alfredo Martínez
Cancers 2024, 16(5), 960; https://doi.org/10.3390/cancers16050960 - 27 Feb 2024
Viewed by 1510
Abstract
Non-coding RNAs provide new opportunities to identify biomarkers that properly classify cancer patients. Here, we study the biomarker status of the mitochondrial long non-coding RNAs, MDL1 and MDL1AS. Expression of these genes was studied in public transcriptomic databases. In addition, a cohort of [...] Read more.
Non-coding RNAs provide new opportunities to identify biomarkers that properly classify cancer patients. Here, we study the biomarker status of the mitochondrial long non-coding RNAs, MDL1 and MDL1AS. Expression of these genes was studied in public transcriptomic databases. In addition, a cohort of 69 locally advanced rectal cancer (LARC) patients with a follow-up of more than 5 years was used to determine the prognostic value of these markers. Furthermore, cell lines of colorectal (HCT116) and breast (MDA-MB-231) carcinoma were employed to study the effects of downregulating MDL1AS in vitro. Expression of MDL1AS (but not MDL1) was significantly different in tumor cells than in the surrounding tissue in a tumor-type-specific context. Both MDL1 and MDL1AS were accurate biomarkers for the 5-year survival of LARC patients (p = 0.040 and p = 0.007, respectively) with promising areas under the curve in the ROC analyses (0.820 and 0.930, respectively). MDL1AS downregulation reduced mitochondrial respiration in both cell lines. Furthermore, this downregulation produced a decrease in growth and migration on colorectal cells, but the reverse effects on breast cancer cells. In summary, MDL1 and MDL1AS can be used as reliable prognostic biomarkers of LARC, and MDL1AS expression provides relevant information on the diagnosis of different cancers. Full article
(This article belongs to the Special Issue Predictive Biomarkers for Colorectal Cancer)
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19 pages, 2824 KiB  
Article
Improved Drug-Response Prediction Model of APC Mutant Colon Cancer Patient-Derived Organoids for Precision Medicine
by Yong Jae Shin, Eun Hae Jo, Yunjeong Oh, Da Som Kim, Seungyoon Hyun, Ahran Yu, Hye Kyung Hong and Yong Beom Cho
Cancers 2023, 15(23), 5531; https://doi.org/10.3390/cancers15235531 - 22 Nov 2023
Cited by 2 | Viewed by 1208
Abstract
Colorectal cancer is the third most common cancer in the world, with an annual incidence of 2 million cases. The success of first-line chemotherapy plays a crucial role in determining the disease outcome. Therefore, there is an increasing demand for precision medicine to [...] Read more.
Colorectal cancer is the third most common cancer in the world, with an annual incidence of 2 million cases. The success of first-line chemotherapy plays a crucial role in determining the disease outcome. Therefore, there is an increasing demand for precision medicine to predict drug responses and optimize chemotherapy in order to increase patient survival and reduce the related side effects. Patient-derived organoids have become a popular in vitro screening model for drug-response prediction for precision medicine. However, there is no established correlation between oxaliplatin and drug-response prediction. Here, we suggest that organoid culture conditions can increase resistance to oxaliplatin during drug screening, and we developed a modified medium condition to address this issue. Notably, while previous studies have shown that survivin is a mechanism for drug resistance, our study observed consistent survivin expression irrespective of the culture conditions and oxaliplatin treatment. However, clusterin induced apoptosis inhibition and cell survival, demonstrating a significant correlation with drug resistance. This study’s findings are expected to contribute to increasing the accuracy of drug-response prediction in patient-derived APC mutant colorectal cancer organoids, thereby providing reliable precision medicine and improving patient survival rates. Full article
(This article belongs to the Special Issue Predictive Biomarkers for Colorectal Cancer)
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10 pages, 738 KiB  
Article
Monitoring Metastatic Colorectal Cancer Progression According to Reactive Oxygen Metabolite Derivative Levels
by Katsuji Sawai, Takanori Goi, Youhei Kimura and Kenji Koneri
Cancers 2023, 15(23), 5517; https://doi.org/10.3390/cancers15235517 - 22 Nov 2023
Viewed by 726
Abstract
Oxidative stress has been implicated in the development, proliferation, and metastasis of colorectal cancer, but few studies have considered how oxidative stress changes in relation to treatment response. In this study, we investigated whether the rate of change in reactive oxygen metabolite derivatives [...] Read more.
Oxidative stress has been implicated in the development, proliferation, and metastasis of colorectal cancer, but few studies have considered how oxidative stress changes in relation to treatment response. In this study, we investigated whether the rate of change in reactive oxygen metabolite derivatives (d-ROM)—serum markers of oxidative stress—could predict treatment response in metastatic colorectal cancer. We enrolled 53 patients with metastatic colorectal cancer who were treated with 3 months of chemotherapy. We measured d-ROM levels and performed computed tomography before and after chemotherapy, and we examined the change in d-ROM levels for each anticancer treatment. Factors influencing the d-ROM ratio (post-treatment: pre-treatment levels) were examined using linear regression analysis. d-ROM levels decreased in patients showing a partial response (p < 0.001) and increased in those showing disease progression (p = 0.042). An increasing d-ROM ratio was associated with disease progression (regression coefficient: 0.416, 95% confidence interval: 0.279–0.555, p < 0.001). Our study indicates that d-ROM levels are useful markers of tumor progression and that the d-ROM ratio is useful for predicting treatment response in patients with metastatic colorectal cancer. Full article
(This article belongs to the Special Issue Predictive Biomarkers for Colorectal Cancer)
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Review

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15 pages, 1117 KiB  
Review
Digital Pathology for Better Clinical Practice
by Assia Hijazi, Carlo Bifulco, Pamela Baldin and Jérôme Galon
Cancers 2024, 16(9), 1686; https://doi.org/10.3390/cancers16091686 - 26 Apr 2024
Viewed by 345
Abstract
(1) Background: Digital pathology (DP) is transforming the landscape of clinical practice, offering a revolutionary approach to traditional pathology analysis and diagnosis. (2) Methods: This innovative technology involves the digitization of traditional glass slides which enables pathologists to access, analyze, and share high-resolution [...] Read more.
(1) Background: Digital pathology (DP) is transforming the landscape of clinical practice, offering a revolutionary approach to traditional pathology analysis and diagnosis. (2) Methods: This innovative technology involves the digitization of traditional glass slides which enables pathologists to access, analyze, and share high-resolution whole-slide images (WSI) of tissue specimens in a digital format. By integrating cutting-edge imaging technology with advanced software, DP promises to enhance clinical practice in numerous ways. DP not only improves quality assurance and standardization but also allows remote collaboration among experts for a more accurate diagnosis. Artificial intelligence (AI) in pathology significantly improves cancer diagnosis, classification, and prognosis by automating various tasks. It also enhances the spatial analysis of tumor microenvironment (TME) and enables the discovery of new biomarkers, advancing their translation for therapeutic applications. (3) Results: The AI-driven immune assays, Immunoscore (IS) and Immunoscore-Immune Checkpoint (IS-IC), have emerged as powerful tools for improving cancer diagnosis, prognosis, and treatment selection by assessing the tumor immune contexture in cancer patients. Digital IS quantitative assessment performed on hematoxylin–eosin (H&E) and CD3+/CD8+ stained slides from colon cancer patients has proven to be more reproducible, concordant, and reliable than expert pathologists’ evaluation of immune response. Outperforming traditional staging systems, IS demonstrated robust potential to enhance treatment efficiency in clinical practice, ultimately advancing cancer patient care. Certainly, addressing the challenges DP has encountered is essential to ensure its successful integration into clinical guidelines and its implementation into clinical use. (4) Conclusion: The ongoing progress in DP holds the potential to revolutionize pathology practices, emphasizing the need to incorporate powerful AI technologies, including IS, into clinical settings to enhance personalized cancer therapy. Full article
(This article belongs to the Special Issue Predictive Biomarkers for Colorectal Cancer)
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17 pages, 1340 KiB  
Review
Prediction of Response to Anti-Angiogenic Treatment for Advanced Colorectal Cancer Patients: From Biological Factors to Functional Imaging
by Giuseppe Corrias, Eleonora Lai, Pina Ziranu, Stefano Mariani, Clelia Donisi, Nicole Liscia, Giorgio Saba, Andrea Pretta, Mara Persano, Daniela Fanni, Dario Spanu, Francesca Balconi, Francesco Loi, Simona Deidda, Angelo Restivo, Valeria Pusceddu, Marco Puzzoni, Cinzia Solinas, Elena Massa, Clelia Madeddu, Clara Gerosa, Luigi Zorcolo, Gavino Faa, Luca Saba and Mario Scartozziadd Show full author list remove Hide full author list
Cancers 2024, 16(7), 1364; https://doi.org/10.3390/cancers16071364 - 30 Mar 2024
Viewed by 748
Abstract
Colorectal cancer (CRC) is a leading tumor worldwide. In CRC, the angiogenic pathway plays a crucial role in cancer development and the process of metastasis. Thus, anti-angiogenic drugs represent a milestone for metastatic CRC (mCRC) treatment and lead to significant improvement of clinical [...] Read more.
Colorectal cancer (CRC) is a leading tumor worldwide. In CRC, the angiogenic pathway plays a crucial role in cancer development and the process of metastasis. Thus, anti-angiogenic drugs represent a milestone for metastatic CRC (mCRC) treatment and lead to significant improvement of clinical outcomes. Nevertheless, not all patients respond to treatment and some develop resistance. Therefore, the identification of predictive factors able to predict response to angiogenesis pathway blockade is required in order to identify the best candidates to receive these agents. Unfortunately, no predictive biomarkers have been prospectively validated to date. Over the years, research has focused on biologic factors such as genetic polymorphisms, circulating biomarkers, circulating tumor cells (CTCs), circulating tumor DNA (ctDNA), and microRNA. Moreover, research efforts have evaluated the potential correlation of molecular biomarkers with imaging techniques used for tumor assessment as well as the application of imaging tools in clinical practice. In addition to functional imaging, radiomics, a relatively newer technique, shows real promise in the setting of correlating molecular medicine to radiological phenotypes. Full article
(This article belongs to the Special Issue Predictive Biomarkers for Colorectal Cancer)
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