Announcements

The 2025 CiteScore metrics have been officially released by Scopus, and the results confirm what has become a consistent pattern for MDPI's journal portfolio: broad recognition across disciplines, steady improvement across the majority of ranked titles, and a growing presence at the top of subject category rankings.

CiteScore, published annually by Elsevier's Scopus database, measures the average citations received by articles published in a journal over a four-year window. As a complement to the Journal Impact Factor, which uses a two-year window based on the Web of Science database, CiteScore provides an alternative, long-term perspective on citation performance.

The 365 MDPI journals in Scopus (as of May 2026) are indexed across a wide range of subject categories, ensuring that open access research remains highly discoverable to a global readership through one of the most widely used platforms in academic publishing.

Data Summary (2025 CiteScores)

• New Additions: 41 MDPI journals received a CiteScore for the first time.
• Trending Upward: 234 of 322 previously ranked journals (73%) saw an increase in their CiteScore compared to last year.
• High Visibility: 314 journals (86%) rank in Q1 or Q2 in at least one subject category.
• Elite Performance: 42 journals rank in the top 10% of their subject categories.

Portfolio Performance

Among the 322 journals that held a CiteScore in 2024, 234 saw an increase this year. Quartile improvements outnumbered declines across the portfolio, with 52 journals moving to a higher quartile and only 20 seeing a decline. Furthermore, no previously ranked journals were removed. The 42 journals now ranked in the top 10% of their subject categories are drawn from a strong foundation of 178 journals holding a Q1 position.

With the large majority of our indexed portfolio ranked in the top half of research fields, researchers can confidently choose MDPI to meet funder mandates for high-quality, fully compliant Open Access publishing.

Exceptional Achievements for Foods and Life

Notably, both Foods and Life achieved a 99th percentile ranking in their respective subject categories for the 2025 CiteScores. This outstanding placement positions them as leading journals in their fields and highlights the high visibility and global impact of the open access research they publish.

Journal Metrics and Beyond

Journal-level metrics describe outlets, not individual articles. An increasing number of funders and institutions—including signatories of DORA and the Coalition for Advancing Research Assessment—now explicitly encourage evaluation at the article level rather than by the journal in which research appears. MDPI supports this direction: we report CiteScore alongside the Journal Impact Factor, Journal Citation Indicator, and article-level usage data because no single number captures the full reach and contribution of published research.

Thank You

These results reflect the sustained effort of thousands of editors-in-chief, editorial board members, reviewers, and authors across every field MDPI serves. The metrics are the outcome; the work is yours.

We had the pleasure of speaking with Dr. Zhenyun Yang, the first and corresponding author of an Editor’s Choice Article in Cancers (ISSN: 2072-6694). Below, he shares insights into his research focus, his paper, challenges encountered, emerging trends, and practical advice.

“Urinary Biomarkers in Bladder Cancer: FDA-Approved Tests and Emerging Tools for Diagnosis and Surveillance”
by Zhenyun Yang, Fengyu Song and Jin Zhong
Cancers 2025, 17(21), 3425; https://doi.org/10.3390/cancers17213425
Available online: https://www.mdpi.com/2072-6694/17/21/3425

The following is an interview with Dr. Zhenyun Yang:

1. Could you briefly introduce yourself and describe your main research focus?
I am an Associate Professor in the Department of Internal Medicine, with research interests centered on clinical anatomy, pathology, histopathology, advanced cancer biomarkers, and emerging diagnostic technologies. My work focuses on translating laboratory and pathological findings into clinically meaningful tools that can improve cancer diagnosis, surveillance, and patient outcomes. In recent years, I have also become increasingly interested in the integration of artificial intelligence, digital pathology, and computational biomarker analysis into precision oncology.

2. In your own words, what are the key findings or main messages of your Editor’s Choice Article?
The main message of our Editor’s Choice Article, “Urinary Biomarkers in Bladder Cancer: FDA-Approved Tests and Emerging Tools for Diagnosis and Surveillance”, is that urinary biomarkers are becoming increasingly important in the diagnosis and surveillance of bladder cancer. While cystoscopy remains the gold standard, it is invasive, costly, and uncomfortable for patients. Our review highlights both FDA-approved urinary tests and emerging molecular tools, including genomic and AI-assisted analytical approaches, that may improve sensitivity, specificity, and patient compliance. We also emphasize that combining biomarkers, machine learning models, and clinical evaluation may help move the field toward more personalized and less invasive bladder cancer management.

3. What current developments in your area of expertise are most exciting to you?
One of the most exciting developments in this area is the rapid integration of molecular diagnostics, artificial intelligence, and digital health technologies into oncology. Advances in liquid biopsy technologies, urinary DNA and RNA analysis, next-generation sequencing, and multi-omics approaches are creating opportunities for earlier detection and more accurate monitoring of bladder cancer recurrence. AI-driven image analysis and predictive algorithms are also transforming pathology and clinical decision-making by improving diagnostic accuracy and identifying patterns that may not be easily recognized through traditional methods. These innovations are accelerating the transition toward precision oncology and individualized patient care.

4. What were the biggest challenges you encountered during this study, and how did you overcome them?
One of the biggest challenges in this study was synthesizing a rapidly expanding body of literature while maintaining clinical relevance and scientific rigor. The field of urinary biomarkers and AI-assisted diagnostics is evolving very quickly, with many emerging assays and computational tools showing promising but sometimes inconsistent results across studies. Another challenge was evaluating technologies that are innovative but not yet fully standardized in clinical practice. We addressed these issues by carefully reviewing the quality of evidence, comparing FDA-approved tests with investigational tools, and emphasizing clinically actionable findings that may realistically impact patient care.

5. How do you see this research evolving or influencing future studies in the field?
I believe this research will contribute to the continued transition toward noninvasive and technology-driven cancer diagnostics and surveillance strategies. Future studies will likely focus on validating biomarker panels in larger multicenter trials, integrating AI-based predictive models into routine clinical workflows, and improving the cost-effectiveness and accessibility of advanced molecular testing. I also anticipate stronger collaboration between clinicians, pathologists, bioinformaticians, and AI researchers to develop smarter diagnostic systems that can support earlier detection and personalized treatment planning.

6. What advice would you give to early career researchers who aim to publish impactful work in oncology?
My advice to early career researchers in oncology is to remain scientifically curious and open to interdisciplinary collaboration, especially as AI and computational medicine become increasingly integrated into healthcare research. Strong research begins with clinically meaningful questions, but impactful studies today often require collaboration across medicine, pathology, data science, and biotechnology. I would encourage young researchers to build strong foundations in research methodology and scientific writing while also becoming familiar with emerging technologies such as digital pathology, bioinformatics, and artificial intelligence. The future of oncology research will likely depend heavily on the ability to combine clinical insight with technological innovation.

7. If you could go back to the very beginning of your research career, what advice would you give to your younger self?
If I could give advice to my younger self, I would say: be patient and embrace continuous learning, especially as science and technology evolve so rapidly. Early in my career, I focused heavily on traditional academic milestones, but I now appreciate the importance of adaptability and interdisciplinary thinking. I would encourage my younger self to explore emerging technologies earlier, including computational medicine and AI, because these tools are increasingly shaping the future of diagnostics and biomedical research. At the same time, I would also emphasize maintaining balance outside the lab and clinic, because long-term success in science depends not only on productivity, but also on resilience, mentorship, curiosity, and personal well-being.

Editor’s Choice Articles are selected based on suggestions from Cancers’ Academic Editors worldwide. The Editors select a small number of recently published articles that they consider particularly interesting to our readers or important in their respective fields of research. You are welcome to read the Editor’s Choice Articles and Speclal Issues related to “Clinical Research of Cancer”.

The list of relevant papers can be seen below:

“Efficiency of Fulvestrant Monotherapy After CDK4/6 Inhibitor Exposure: Is This a Viable Choice?”
by Nanae Ogata, Brian G Barnett, Nicholas J.H. Sharp, Takeo Fujii, Toshiaki Iwase, Sandra E. Dunn and Naoto T. Ueno
Cancers 2025, 17(5), 884; https://doi.org/10.3390/cancers17050884
Available online: https://www.mdpi.com/2072-6694/17/5/884

“The Safety of Abiraterone Acetate in Patients with Metastatic Castration-Resistant Prostate Cancer: An Individual-Participant Data Meta-Analysis Based on 14 Randomized Clinical Trials”
by Amy L. Shaver, Nikita Nikita, Swapnil Sharma, Scott W. Keith, Kevin K. Zarrabi, Wm. Kevin Kelly and Grace Lu-Yao
Cancers 2025, 17(17), 2747; https://doi.org/10.3390/cancers17172747
Available online: https://www.mdpi.com/2072-6694/17/17/2747

“Impact of Membranous Nectin-4 on Outcomes of Platinum-Based Chemotherapy in Metastatic Urothelial Carcinoma”
by Fu-Jen Hsueh, Chung-Chieh Wang, Jhe-Cyuan Guo, Shih-Chieh Chueh, Yu-Chieh Tsai
Cancers 2025, 17(3), 433; https://doi.org/10.3390/cancers17030433
Available online: https://www.mdpi.com/2072-6694/17/3/433

“Immunotherapy-Induced Complete Response in dMMR Rectal Cancer. A Surgical Dilemma?”
by Panagiotis Loufopoulos, Konstantinos Perivoliotis, Danai Chatziathanasiou, Maximos Frountzas, Anisha Sukha, Abdullah Alrebdi, Mohammad Mahmoud Rajab Eddama, Christos Kontovounisios, Shengyang Qiu, Paris Tekkis et al.
Cancers 2025, 17(19), 3153; https://doi.org/10.3390/cancers17193153
Available online: https://www.mdpi.com/2072-6694/17/19/3153

“Advanced External Beam Stereotactic Radiotherapy for Skull Base Reirradiation”
by He Wang, Fahed M. Alsanea, Dong Joo Rhee, Xiaodong Zhang, Wei Liu, Jinzhong Yang, Zhifei Wen, Yao Zhao, Tyler D. Williamson, Rachel A. Hunter et al.
Cancers 2025, 17(3), 540; https://doi.org/10.3390/cancers17030540
Available online: https://www.mdpi.com/2072-6694/17/3/540

“Phase II Study of Atezolizumab and Bevacizumab Combination Therapy for Patients with Advanced Hepatocellular Carcinoma Previously Treated with Lenvatinib”
by Takeshi Terashima, Hidenori Kido, Noboru Takata, Tomoyuki Hayashi, Akihiro Seki, Hidetoshi Nakagawa, Kouki Nio, Tadashi Toyama, Noriho Iida, Shinya Yamada et al.
Cancers 2025, 17(2), 278; https://doi.org/10.3390/cancers17020278
Available online: https://www.mdpi.com/2072-6694/17/2/278

“Treatment Approaches for Oligoprogressive Non-Small Cell Lung Cancer: A Review of Ablative Radiotherapy”
by William Gombrich, Nicholas Eustace, Yufei Liu, Ramya Muddasani, Adam Rock, Ravi Salgia, Terence Williams, Jyoti Malhotra, Percy Lee and Arya Amini
Cancers 2025, 17(7), 1233; https://doi.org/10.3390/cancers17071233
Available online: https://www.mdpi.com/2072-6694/17/7/1233

“Regenerative Immunotherapy for Cancer: Transcription Factor Reprogramming of Tumor-Specific T Cells”
by Tyler R. McCaw, Nicholas P. Restifo, Kathrin Plath and Joseph G. Crompton.
Cancers 2025, 17(13), 2225; https://doi.org/10.3390/cancers17132225
Available online: https://www.mdpi.com/2072-6694/17/13/2225

Special Issues:

“Thyroid Cancer Recurrence: Integrating Surgical, Clinical, and Translational Research”
Guest Editors: Prof. Dr. Nikola Slijepcevic and Prof. Dr. Ioannis Koutelidakis
Submission deadline: 20 October 2026

“Clinical Research in Ocular Oncology”
Guest Editors: Dr. Anthony Daniels, Dr. Arun D. Singh and Prof. Dr. Jens Folke Kiilgaard
Submission deadline: 31 October 2026

“Real-World Clinical Studies in Acute Leukemia”
Guest Editor: Prof. Dr. Anna Candoni
Submission deadline: 31 December 2026

“Laparoscopic and Robotic Surgery for Gastrointestinal and Hepato-Pancreato-Biliary Cancers”
Guest Editor: Dr. Kosei Takagi
Submission deadline: 31 December 2026

You are invited to view and submit relevant papers to the journal Cancers at the following link:
https://www.mdpi.com/journal/cancers.

We had the pleasure of speaking with Dr. Angie Fasoula, the first and corresponding author of the Editor’s Choice Article in Cancers (ISSN: 2072-6694). Here, she shares her motivation, sources of inspiration, research journey, and insights into future research.

“Wavelia Microwave Breast Imaging Phase#2 Clinical Investigation: Methodological Evolutions and Multidimensional Radiomics Analysis Towards Controlled Specificity”
by Angie Fasoula, Giannis Papatrechas, Petros Arvanitis, Luc Duchesne, Julio Daniel Gil Cano, John O’Donnell, Sami Abd Elwahab and Michael Kerin
Cancers 2025, 17(18), 2973; https://doi.org/10.3390/cancers17182973
Available online: https://www.mdpi.com/2072-6694/17/18/2973

The following is an interview with Dr. Angie Fasoula.

1. Could you briefly introduce yourself and describe your main research focus?

I am a biomedical/microwave radar engineer, with a PhD in electrical and computer engineering (TUDelft, NL) and nearly 20 years of research and industrial experience in microwave system engineering, radar signal processing and microwave medical imaging, including leading the full development cycle of the Wavelia Microwave Breast Imaging system from concept to clinical trials. I am currently CTO and Co-Founder of MIMA Technologies, a deep-tech medical device startup, developing a next-generation, non-ionizing, compression-free, 3D breast imaging scanner based on microwave radar technology. Our mission is to advance diagnostic accuracy and democratize early diagnosis of cancer, particularly in the underserved population of women with dense breasts.

2. What inspired you to pursue this particular area of cancer research?

Breast cancer is the most common malignancy in women and the second cause of cancer-related deaths. Early detection dramatically improves survival rates, yet current diagnostic technologies face critical limitations: low sensitivity in dense breast tissue and early-stage cancers (mammography detects only ~62-68% in dense breasts); radiation exposure: ionising radiation from mammography makes frequent screening unsafe; high cost and complexity: MRI offers better sensitivity but is expensive, requires contrast agents, and causes discomfort, limiting accessibility; painful compression and claustrophobic procedures deter participation, resulting in ~40% of eligible women in Europe skipping routine breast screening!

Unlike mammography or MRI, Microwave Breast Imaging (MWBI) eliminates radiation risks and painful compression while showing potential for enhanced sensitivity in dense breast tissue and early-stage cancers. In addition, by integrating radar-based (semi-)automated lesion reporting and malignancy scoring, clear potential to reduce radiologist workload and improve workflow efficiency, rendering the modality cost-effective and scalable for widespread adoption, opens up.

Several years ago, I got strongly motivated and persuaded to focus my research on the Microwave Breast Imaging (MWBI) technology and clinical research, driven by the belief that by addressing the aforementioned diagnostic gaps in breast imaging, the MWBI modality holds considerable promise for increasing screening participation, enabling earlier detection, and reducing healthcare costs, thus unlocking access for millions of women currently underserved by existing technologies.

3. In your own words, what are the key findings or main messages of your Editor’s Choice Article?

This study provided overall foundational data, contributing to the rationalization of the MWBI imaging and image analysis outputs, towards standardization, objective interpretability, and ultimate clinical acceptance.

By transitioning from the initial Wavelia#1 Microwave Breast Imaging (MWBI) prototype to the more advanced Wavelia #2 prototype, we have successfully demonstrated in the study that this technology can accurately distinguish between malignant and benign lesions across a more diverse patient population. Moving beyond the three basic features used in the initial study to a multidimensional radiomic approach, the new prototype leveraged complex texture and intensity data to improve the accuracy of lesion classification.

In addition, the qualitative assessment of false positive rates in healthy breasts marks a milestone for this technology, providing the first real-world look at how the system maintains accuracy without over-diagnosing healthy tissue.

4. What were the biggest challenges you encountered during this study, and how did you overcome them?

The clinical investigation of the Wavelia #2 prototype identified critical challenges in aligning microwave imaging (MWBI) results with traditional radiological references due to variations in breast positioning. In several cases, the detected Regions of Interest (ROIs) did not immediately align with the expected clinical and radiological locations within the breast. In the frame of this exploratory study, the system's internal camera views were used to help reconcile such positional discrepancies, providing a visual reference for how the breast was positioned during the scan. To achieve clinical acceptance, future developments will need to focus on standardizing patient positioning and improving the objective interpretability of MWBI scans compared to traditional mammography or ultrasound.

This study also marked the first-ever attempt to identify recurring Microwave Breast Imaging artifacts and categorize them based on their recognizable patterns. Such research required intensive, long-form review sessions where clinical investigators and study radiologists performed side-by-side comparisons of the MWBI datasets against reference imaging. This collaborative, detailed review was essential to (a) establish pattern recognition: distinguishing true biological signals from mechanical or algorithmic artifacts, and (b) ensure radiological alignment: confirming that the MWBI findings correlated with established clinical standards. Only after isolating the recurring imaging artifacts, we were able to conduct a meaningful preliminary analysis of the system's specificity within asymptomatic breasts.

5. How do you see this research evolving or influencing future studies in the field?

Our study highlighted MWBI as a significant area of interest in the future of breast cancer diagnostics. The absence of radiation and the potential for use in dense breasts positions this technology at the forefront of future screening interventions in younger women. Technological advances, reduced screening time and application of artificial intelligence are expected to open possibilities for major clinical applications. Finally, while breast imaging is the current main area of interest, this technology also has potential in diagnostic imaging of other superficial soft-tissue organs, such as the thyroid.

Ms. Abigayle (Abbey) Vito, a third-year graduate student in Dr. Bret Freudenthal’s lab at the University of Kansas Medical Center, won the poster award at the 7th DNA Repair/Replication Structures & Cancer Conference, sponsored by the Journal Cluster of Oncology, and we had the privilege of speaking with her. Below, she shares insights into her academic journey, research focus, and the motivation behind her landmark study.

1. Could you briefly introduce yourself and your main research focus within the broad area of DNA repair, replication structures, or cancer biology?
My name is Abigayle (Abbey) Vito, and I am a third-year graduate student in Dr. Bret Freudenthal’s lab at the University of Kansas Medical Center. My research focuses on understanding how DNA repair occurs within the complex chromatin environment of human cells. Much of the biochemical work that has laid the foundation for our knowledge of DNA repair has been performed on short DNA oligonucleotides. However, DNA in human cells is much more complex and is condensed into chromatin through the fundamental unit known as the nucleosome. My research goal is to understand how DNA repair, specifically base excision repair (BER), operates within chromatin. To address this goal, I utilize the nucleosome as a model system and use structural biology to elucidate the molecular mechanism that BER enzymes use to engage their substrates. This work fundamentally enhances our understanding of how DNA repair is carried out within human cells. 
 
2. What do you think made your poster stand out—the scientific novelty, the clarity of the story, the visual presentation, or something else?
It was an incredible experience to attend a conference with so many structural biologists, from trainees to experts in the field. Based on the feedback I received during the poster session, I believe that my poster stood out for its clarity and the number of novel structures presented. I think, as structural biologists, we get very excited to see new structures from other researchers in the field because they can provide a lot of new insight into proteins that we are invested in understanding.
 
3. Any advice for early career researchers preparing their first poster?
The most important piece of advice that I have received about making a poster is that it is not necessary to present every piece of data that you have collected. It is much more impactful to have a visually appealing poster with a logical flow and only share the most important aspects of your story. Getting to the central point of your story quickly allows time for more meaningful conversations with audience members, which can lead to new perspectives on your research or experiments you may be struggling with.
 
4. Looking beyond the poster, what are the next steps for this research? Are you planning to follow up with a full paper?
This poster was only the beginning of a very exciting project! Along with structural data showing how BER enzymes engage their substrates, I am very interested in understanding how these enzymes locate their substrates to begin with. The nucleus of human cells contains over 3 billion base pairs of DNA, and these proteins face the extraordinarily difficult task of finding the specific lesion that they need to process. We are excited to use a single-molecule approach to investigate the mechanisms used by BER proteins to search for DNA damage. Looking further ahead, we hope to translate this into human cells to better understand how these enzymes protect against DNA-damaging agents that drive cancer. 
 
5. Our journal has always been committed to promoting high-quality research in DNA repair/replication and cancer biology. Would you be interested in working with us? What kind of support would be most helpful for you in that process?
I would absolutely be interested in working with the journal! As my project develops, I hope to submit a research article encompassing both the structural and single-molecule findings from this work. Having a journal with a strong commitment to DNA repair and cancer biology would be a great fit for this story. As for support, having guidance through the submission and revision process would be most helpful. In particular, workshops that address the technical aspects of manuscript submission and the editorial/peer review process would be very beneficial for early-career researchers like myself.

Editor’s Choice Articles are selected based on suggestions from Cancers’ Academic Editors worldwide. The Editors select a small number of recently published articles that they consider particularly interesting to our readers or important in their respective fields of research. You are welcome to read the Editor’s Choice Articles and Special Issues related to cancer pathophysiology, a curated list of high-quality articles published in 2025 in Cancers (ISSN: 2072-6694). The full list of Editor’s Choice Articles can be viewed at the following link: https://www.mdpi.com/journal/cancers/editors_choice.

The list of relevant papers can be seen below:

“Total Neoadjuvant Therapy for Locally Advanced Rectal Cancer: Evaluation of Sequencing, Response, and Toxicity in a Single-Institution Cohort”
by Maria Cristina Barba, Paola De Franco, Donatella Russo, Elisa Cavalera, Elisa Ciurlia, Sara De Matteis, Giuseppe Di Paola, Corradino Federico, Angela Leone, Antonella Papaleo et al.
Cancers 2025, 17(15), 2416; https://doi.org/10.3390/cancers17152416
Available online: https://www.mdpi.com/2072-6694/17/15/2416

“Tristetraprolin Family Members and Processing Bodies: A Complex Regulatory Network Involved in Fatty Liver Disease, Viral Hepatitis and Hepatocellular Carcinoma”
by Noémie Gellée, Noémie Legrand, Mickaël Jouve, Pierre-Jean Devaux, Laurent Dubuquoy and Cyril Sobolewski
Cancers 2025, 17(3), 348; https://doi.org/10.3390/cancers17030348
Available online: https://www.mdpi.com/2072-6694/17/3/348

“Comprehensive Molecular Profiling of Metastatic Pancreatic Adenocarcinomas”
by Vijay Antony, Tong Sun, Darin Dolezal and Guoping Cai
Cancers 2025, 17(3), 335; https://doi.org/10.3390/cancers17030335
Available online: https://www.mdpi.com/2072-6694/17/3/335

“Epitranscriptomics in the Glioma Context: A Brief Overview”
by Pablo Santamarina-Ojeda, Agustín F. Fernández and Mario F. Fraga
Cancers 2025, 17(4), 578; https://doi.org/10.3390/cancers17040578
Available online: https://www.mdpi.com/2072-6694/17/4/578

“Sexual-Sparing Radical Cystectomy in the Robot-Assisted Era: A Review on Functional and Oncological Outcomes”
by Carlo Introini, Manfredi Bruno Sequi, Marco Ennas, Andrea Benelli, Giovanni Guano, Antonio Luigi Pastore and Antonio Carbone
Cancers 2025, 17(1), 110; https://doi.org/10.3390/cancers17010110
Available online: https://www.mdpi.com/2072-6694/17/1/110

“Patient-Derived Meningioma Organoids: A Reliable Model for Studying Human Tumor Pathophysiology”
by Youssef M. Zohdy, Arman Jahangiri, Fadi Jacob, Aliaksandr Aksionau, Ali M. Alawieh, Amelia Tong, Bethany Chern, Justin Maldonado, Kimberly Hoang, Edjah Nduom et al.
Cancers 2025, 17(3), 526; https://doi.org/10.3390/cancers17030526
Available online: https://www.mdpi.com/2072-6694/17/3/526

Special Issues:

You are invited to view and submit relevant papers to the journal Cancers at the following link: https://www.mdpi.com/journal/cancers.

On 8 May 2026, MDPI Canada & USA welcomed over 40 researchers, clinicians, and oncology professionals to our Subject Workshop, “Cutting-Edge Advances in Cancer Immunology and Immunotherapy: From Basic Science to Clinical Impact”, held at the HSC Conference Center in Los Angeles, California.

	Our workshop host, Bob Vrooman, Head of Business Development at MDPI USA, opened the event and emphasized the importance of advancing cancer care. He introduced the workshop chair, Dr. W. Martin Kast, highlighting his achievements in immunology and cancer research.
	Dr. W. Martin Kast welcomed attendees, emphasizing the transformative impact of cancer immunotherapy and the challenges that remain.
	Then, MDPI Canada & USA’s Operating Director, Elvis Wang, emphasized the company's core values of transparency, service, and integrity. Furthermore, he explained the importance of collaboration in scientific research.

The day’s presentations were full of exciting discussion as ten speakers discussed their research findings. These presenters included Dr. Abhinava Mishra, Dr. Alan L. Epstein, Dr. De-Chen Lin, Dr. Casey O’Connell, Dr. Henry K. Wong, Dr. Hossein Jadvar, Dr. Kawaljit Kaur, Dr. Lili Yang, Dr. W. Martin Kast, and Dr. Sonia Sharma.

The presentations included topics such as immune checkpoint blockade therapy, CAR-T and CAR-macrophage therapies, and the role of NK cells in cancer therapy. Furthermore, presentations focused on how epigenetic mutations reshape T-cell behavior.

The second half of the day included presentations covering imaging treatment response criteria and multimodal single-cell analysis. Further presentations focused on the treatment of cutaneous T-cell lymphomas (CTCLs) and the development of therapeutic vaccines to treat HPV-associated cancers.

Dr. Sheridan Baker, a representative of MDPI, covered MDPI's role in supporting open science and MDPI’s publishing trends in oncology. His presentation allowed audience members to further understand how MDPI can support researchers working within a variety of research areas.

During the day’s proceedings, multiple Q&A sessions were held, allowing valuable engagement between speakers and attendees. These sessions were a highlight of the event and helped build a platform for meaningful scientific exchange.

Looking Ahead

The MDPI 2026 LA Subject Workshop “Cutting-Edge Advances in Cancer Immunology and Immunotherapy: From Basic Science to Clinical Impact” was a successful collaboration between MDPI and local academics. We are thankful to all attendees for their part in making this event possible and for contributing to its success.

We have received positive feedback regarding this event and look forward to continuing to host these Subject Workshops. For more updates regarding this event and other upcoming workshops, follow MDPI Canada on LinkedIn.

We are delighted to share a collection of highly viewed papers in cancer causes, screening and diagnosis that were published in Cancers (ISSN: 2072-6694) in 2025. In addition, some Special Issues on this topic are currently open for submission. The following is a list of articles and Special Issues that we believe may be of interest to you:

The list of relevant papers can be seen below:

1. “CAR-T Cell Therapies in B-Cell Acute Lymphoblastic Leukemia: Emerging Data and Open Issues”
by Caterina Alati, Martina Pitea, Matteo Molica, Luca Scalise, Gaetana Porto, Erica Bilardi, Giuseppe Lazzaro, Maria Caterina Micò, Marta Pugliese, Filippo Antonio Canale et al.
Cancers 2025, 17(18), 3027; https://doi.org/10.3390/cancers17183027
Available online: https://www.mdpi.com/2072-6694/17/18/3027

2. “Next-Generation Therapies in Mantle Cell Lymphoma (MCL): The Evolving Landscape in Treatment of Relapse/Refractory After CAR-T Cells”
by Elia Boccellato, Lorenzo Comba, Rita Tavarozzi, Claudia Castellino, Myriam Foglietta, Daniele Mattei, Marco Ladetto, Massimo Massaia and Alessia Castellino
Cancers 2025, 17(13), 2239; https://doi.org/10.3390/cancers17132239
Available online: https://www.mdpi.com/2072-6694/17/13/2239

3. “Neoadjuvant, Perioperative, and Adjuvant Immunotherapy in Early-Stage Surgically Resectable Non-Small Cell Lung Cancer: Updates and Future Perspectives”
by Diamone Gathers, Cameron Oswalt, Laura Alder, Kevin Chen, Jordyn P. Higgins, Jeffrey M. Clarke and Eziafa I. Oduah
Cancers 2025, 17(13), 2077; https://doi.org/10.3390/cancers17132077
Available online: https://www.mdpi.com/2072-6694/17/13/2077

4. “Immunotherapy for High-Grade Gliomas”
by Nishika Karbhari, Kelsey M. Frechette, Terry C. Burns, Ian F. Parney, Jian L. Campian, William G. Breen, Ugur T. Sener and Eric J. Lehrer
Cancers 2025, 17(11), 1849; https://doi.org/10.3390/cancers17111849
Available online: https://www.mdpi.com/2072-6694/17/11/1849

5. “Management of Triple M Syndrome: A Narrative Review of Immune Checkpoint Inhibitor-Induced Myasthenia Gravis, Myositis and Myocarditis”
by Martin Furlepa, Isabella Watts and Aisling S. Carr
Cancers 2025, 17(13), 2063; https://doi.org/10.3390/cancers17132063
Available online: https://www.mdpi.com/2072-6694/17/13/2063

6. “Immunohistochemistry for Skin Cancers: A Comprehensive Approach to the Diagnosis of Squamous Cell Carcinoma”
by Vlad-Mihai Voiculescu, Radu-Marian Marinescu, Sorin Dutulescu and Florica Stăniceanu
Cancers 2025, 17(10), 1629; https://doi.org/10.3390/cancers17101629
Available online: https://www.mdpi.com/2072-6694/17/10/1629

7. “From Spice to Survival: The Emerging Role of Curcumin in Cancer Immunotherapy”
by Jacob M. Parker, Lei Zhao, Trenton G. Mayberry, Braydon C. Cowan, Mark R. Wakefield and Yujiang Fang
Cancers 2025, 17(15), 2491; https://doi.org/10.3390/cancers17152491
Available online: https://www.mdpi.com/2072-6694/17/15/2491

8. “The Quest for Non-Invasive Diagnosis: A Review of Liquid Biopsy in Glioblastoma”
by Maria George Elias, Harry Hadjiyiannis, Fatemeh Vafaee, Kieran F. Scott, Paul de Souza, Therese M. Becker and Shadma Fatima
Cancers 2025, 17(16), 2700; https://doi.org/10.3390/cancers17162700
Available online: https://www.mdpi.com/2072-6694/17/16/2700

Special Issues:

1. “Cellular Immunotherapy for Leukemias—Advances, Limitations, and the Path Forward” Guest Editors: Dr. Lohith Gowda and Prof. Dr. Stuart E. Seropian Submission deadline: 30 June 2026	2. “Exploring Immunotherapy in Colorectal Cancer” Guest Editors: Dr. Alessandro Passardi and Dr. Luca Esposito Submission deadline: 30 June 2026
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We had the pleasure of speaking with Dr. Miguel Esperança-Martins, the first and corresponding author of an Editor’s Choice Article in Cancers (ISSN: 2072-6694). Here, he shares insights into his paper, research focus, area of expertise and insights.

“Transcriptomic-Based Classification Identifies Prognostic Subtypes and Therapeutic Strategies in Soft Tissue Sarcomas”
by Miguel Esperança-Martins, Hugo Vasques, Manuel Sokolov Ravasqueira, Maria Manuel Lemos, Filipa Fonseca, Diogo Coutinho, Jorge Antonio López, Richard S. P. Huang, Sérgio Dias, Lina Gallego-Paez et al.
Cancers 2025, 17(17), 2861; https://doi.org/10.3390/cancers17172861
Available online: https://www.mdpi.com/2072-6694/17/17/2861

The following is an interview with Dr. Esperança-Martins.

1. Could you briefly introduce yourself and describe your main research focus?

I am a medical oncologist, an academic and a researcher devoted to sarcomas. The whole team and I who worked on this paper are involved in work at the interface of oncology, computational biology and translational and clinical medicine. We have a particular interest in molecular profiling studies using state-of-the-art multi-omics approaches and in traditional and emerging machine learning models, such as foundation and other generative models. Ultimately, we aim to understand how the use of cutting-edge analytical models to examine granular molecular data can refine sarcoma classification, prognostication and treatment personalization. Our work focuses on integrating genomic, transcriptomic, proteomic, metabolomic and clinical data to better capture clinically meaningful molecular patterns in sarcomas. The broader goal is to help translate complex molecular data into practical tools that can improve patient stratification and support more precise and personalized treatment decisions for sarcomas.

2. In your own words, what are the key findings or main messages of your Editor’s Choice Article?

Firstly, it is crucial to highlight that soft tissue sarcomas' histopathological classification has several conceptual caveats, being indirect, non-specific and prone to errors. The inaccuracy and complexity of this histopathological classification system directly impact prognosis estimation precision, affect therapeutic management and, by adding fragmentation and heterogeneity to sarcoma rarity, hamper drug discovery and drug development in sarcomas. Moreover, current gold-standard clinical (of which the SARCULATOR nomograms are the epitome)- and molecular (of which CINSARC is the best example)-based prognostication tools also display specific methodological limitations.

We conducted a clinically driven molecular profiling study of soft tissue sarcomas, whose data was analyzed using machine learning models with the objective to increase prognostication accuracy and to identify novel molecular targets. More specifically, we undertook the following:

• Novel Cohort and Multi-Omics Profiling: We assembled a novel cohort of over 100 high-grade soft tissue sarcoma samples and performed DNA-seq and RNA-seq to profile 3 of the most common soft tissue sarcoma subtypes (leiomyosarcoma, dedifferentiated liposarcoma and undifferentiated pleomorphic sarcoma).
• Unsupervised Machine Learning Analysis: RNA-seq data was analyzed using unsupervised machine learning models (consensus clustering), uncovering previously unknown molecular patterns and identifying four distinct transcriptomic subtypes with clear prognostic value (notable overall survival (OS) and disease-free survival (DFS) estimating capacity).
• Superior Prognostic Value: Our transcriptomic subtype-based classification outperforms both currently employed clinical-based tools (SARCULATOR nomograms) and gold-standard molecular-based methods (CINSARC) in prognostic accuracy (superior OS predictive capability than SARCULATOR and CINSARC and superior DFS predictive capability than CINSARC), being one of the first molecular-based classifications capable of predicting OS in soft tissue sarcomas. These findings have been externally validated using the TCGA-SARC cohort.
• Actionable Molecular Targets: DNA-seq analysis revealed unique and previously unreported molecular targets across transcriptomic subtypes, highlighting potential opportunities for precision treatment.
• Innovative and Impactful: This new classification system not only provides superior prognostic value but also identifies novel molecular targets for precision treatment. It represents a cutting-edge tool for predicting prognosis and guiding treatment across different stages of soft tissue sarcomas.

Overall, our paper supports the idea that sarcoma classification should evolve from a primarily morphology-based system toward a more dynamic, molecularly informed framework.

We face it as the first layer of a broader precision sarcoma framework: a transcriptomic classifier that can now be expanded into a multi-omics AI-driven platform for prognostication, target discovery and treatment selection.

3. What current developments in your area of expertise are most exciting to you?

The most exciting developments in sarcoma research lie in the rapid expansion of a panoply of increasingly sensitive multi-omics profiling techniques, their exquisite dynamic integration, the development of specialized AI-driven analytical methods and the explosion of AI-driven generative frameworks.

Sarcomas are rare and highly heterogeneous neoplasms, and traditional histopathological classification does not always capture their biological complexity. New genomic tools, including whole-genome sequencing, long-read sequencing, copy-number profiling and mutational signature analysis, are helping us to identify structural variants, fusion events, DNA repair defects and actionable alterations with much higher resolution. At the transcriptomic level, bulk RNA-seq, single-cell RNA-seq and spatial transcriptomics are allowing us to define sarcoma cell states, immune microenvironments and molecular subtypes that may cut across classical histological categories. Proteomics and phosphoproteomics also provide a functional view of pathway activation, kinase signaling and druggable vulnerabilities that may not be evident from DNA or RNA alone. In parallel, metabolomics and lipidomics can reveal altered metabolic dependencies, such as changes in redox balance, amino acid metabolism, lipid signaling and, interestingly, patterns of mitochondrial activity, which may open new therapeutic opportunities.

Traditional machine learning models, such as random forests, XGBoost, survival models and clustering algorithms (among others), remain very useful for prognostication, biomarker discovery and patient stratification. At the same time, emerging foundation (and other generative) models in pathology, genomics, single-cell biology, protein structure and chemistry may help predict molecular subtypes from routine histology, infer gene and pathway perturbations, prioritize therapeutic targets and support in silico drug screening or molecule generation. Globally, there is a whole spectrum of brand-new tools, from lab-in-the-loop models to virtual cell models and in silico perturbation screens, that truly allow us to complete the loop from the patient to a tailored drug design.

I truly believe that the future of sarcoma research will depend on combining multi-omics characterization with interpretable machine-learning-based models, so that we can move from descriptive classification toward mechanism-based prognosis, rational drug discovery and more personalized treatment strategies. The aim has to be centered on molecule generation, via a refined integration of all different modalities.

Ultimately, new types of computing that simulate interactions and mechanisms in atom-level detail will be game changers for cancer research across all the different cancer subtypes.

4. What were the biggest challenges you encountered during this study, and how did you overcome them?

It is invariably difficult to carry out molecular profiling studies of soft tissue sarcomas (rare and highly heterogenous neoplasms) comprising a significant number of samples and a proper representation of the different histotypes. We opted to undertake a retrospective study including a significant number of samples of a well-selected array of the most common subtypes of high-grade soft tissue sarcomas from a single European reference center to overcome some of these conceptual hurdles. It is also hard to have access and to integrate a balanced number of primary tumor and metastases samples and/or to include paired primary and metastases samples, a caveat that is more rigorously tackled by prospective, multicentric, homogenously designed collaborations that follow common samples collection protocols across institutions. We are actively carrying out a coordinated prospective (paired) sample collection across different sarcoma reference centers in Portugal. This also ensures a homogenization of the chronological ages of samples and a harmonized collection of paired fresh tissue and paraffin-embedded samples, a measure that diminishes the heterogeneity in terms of the degree of degradation and of the quality of the biological material for molecular profiling analysis. Finally, the lack of availability of either non-targeted or targeted sequencing tests composed of gene sets whose differential expression profile is characteristic of soft tissue sarcomas is also a limitation that is difficult to cover.

5. How do you see this research evolving or influencing future studies in the field?

This paper establishes a starting framework and is the molecular anchor that still needs to be expanded into a multi-omics, AI-driven sarcoma discovery platform.

The newly identified transcriptomic subtype-based classification, transcriptomic subtypes and transcriptomic subtypes' intrinsic prognostic and predictive value have to be externally validated in larger and different multicentric cohorts other than TCGA-SARC (especially cohorts and datasets whose genomics/transcriptomics profiling was achieved through the employment of sarcoma-specific gene panels).

We have shown that gene expression is able to stratify subtypes and inform therapeutic strategies, reinforcing the idea that technology advances, both in sequencing technologies paired with computational biology methods to harness this data, are the future.

Moreover, it is crucial to build a multi-omics map of sarcoma states, employing state-of-the-art genomics, transcriptomics, proteomics and metabolomics analytical tools and integrating all the data generated by them.

Then, it is fundamental to identify subtype-specific vulnerabilities (using ML and network-specific techniques), to translate into drug discovery (using in silico models, virtual screening, foundation models and generative molecule design) and, finally, to validate everything experimentally.