Exploring the transformative developments in precision oncology, AI, and immunotherapy that are reshaping cancer treatment approaches.
While the journal Applied Cancer Research has paused its regular publications, the field of cancer research is experiencing multiple transformative 'new phases' simultaneously—from novel treatment modalities to conceptual breakthroughs in our understanding of cancer biology.
If you've tried to find the latest issues of Applied Cancer Research recently, you may have discovered something surprising—the journal as many knew it has ceased publication. The official website now simply states that it "ceased to be published by BMC" and directs readers to archives from 2016-2020 1 .
But this quiet transition masks a much larger, more exciting story about the evolution of cancer research itself.
While the journal may have paused its regular publications, the institution behind it—Brazil's A.C. Camargo Cancer Center—continues to be an international reference in cancer diagnosis, treatment, education, and research 7 .
This integrated approach, where "doctors and scientists work together to develop research that will be applied in oncology in the future," represents the very essence of applied cancer research today 7 .
In cancer research, the term 'phase' carries several important meanings. Most familiar are the clinical trial phases (0 through IV) that represent sequential steps in testing new treatments 5 .
Precision oncology represents a fundamental shift from traditional cancer treatment. Instead of categorizing cancers primarily by their location in the body (breast, lung, colon), this approach focuses on the specific genetic mutations and molecular characteristics of an individual's tumor 4 .
"to develop tailored diagnostic and therapeutic solutions using cutting-edge technologies and data, ensuring every patient receives the right treatment at the right time"
Match each patient with treatments that target the unique vulnerabilities of their cancer.
For decades, certain cancer-driving proteins were considered 'undruggable' because their shape made it difficult for medications to bind to them. The KRAS protein was one such notorious target 6 9 .
"We are about to enter a new era for drugging the undruggable with the next generation of mutant-specific molecules"
KRAS considered "undruggable" despite being mutated in 25% of cancers
First-generation KRASG12C inhibitors approved
Research advances to target KRASG12D, KRASG12V variants
Development of pan-KRAS inhibitors underway
AI algorithms can now analyze medical images with remarkable precision, often detecting subtle patterns invisible to the human eye.
For instance, DeepHRD, a deep-learning tool developed at UCSD, can detect homologous recombination deficiency characteristics in tumors using standard biopsy slides 4 .
The drug development process is also benefiting from AI integration.
HopeLLM, introduced in June 2025 by City of Hope, assists physicians in summarizing patient histories, identifying trial matches, and extracting data for research 4 .
This application of AI addresses one of the major bottlenecks in cancer research: identifying eligible patients for clinical trials and efficiently analyzing complex data 4 .
While immune checkpoint inhibitors like pembrolizumab (Keytruda) continue to show promise—with the KEYNOTE-689 trial demonstrating a 34% lower risk of disease recurrence for head and neck cancer patients 4 —research is advancing on multiple immunotherapy fronts.
Bispecific antibodies represent one particularly promising avenue. These innovative therapies work by binding simultaneously to cancer cells and immune cells, effectively bridging them together to help the immune system mount a direct attack on the tumor 4 .
On July 2, 2025, this bispecific antibody was approved for treating relapsed or refractory multiple myeloma in adults who have received at least four prior therapies 4 .
Radiopharmaceuticals combine targeting molecules with radioactive isotopes to deliver radiation directly to cancer cells.
"We see two major themes emerging in 2025 and beyond to transform cancer care: radiopharmaceuticals and conditional immune cell engagers"
In cellular therapies, researchers are working to overcome the limitations of first-generation CAR T-cell treatments.
"The field is realizing that scalability is crucial to increase access"
To understand how precision oncology works in practice, let's examine a seminal study conducted across multiple cancer centers that evaluated patients with breast, lung, and pancreatic cancer 4 .
The results demonstrated the significant potential of precision oncology. Patients who underwent precision medicine interventions showed significantly improved overall survival compared to those who received only standard therapies 4 .
| Cancer Type | Overall Survival Benefit | Key Targeted Mutations |
|---|---|---|
| Breast Cancer | Significant improvement | HRD, BRCA1/2, PIK3CA |
| Lung Cancer | Moderate to strong improvement | EGFR, ALK, ROS1, KRAS |
| Pancreatic Cancer | Emerging improvement | KRAS, BRCA1/2, MSI-H |
| Parameter | Standard Therapy | Precision Oncology |
|---|---|---|
| Treatment Selection Basis | Cancer type and stage | Genetic profile of tumor |
| Biomarker Use | Limited | Comprehensive |
| Personalization Level | Population-based | Individualized |
These findings provide robust evidence that targeting specific molecular alterations across different cancer types can improve patient outcomes—a cornerstone principle of precision oncology 4 .
Modern cancer research relies on an array of sophisticated tools and technologies. Here are some of the most critical ones mentioned in our featured experiment and current literature:
| Tool/Technology | Function | Application in Cancer Research |
|---|---|---|
| Next-Generation Sequencing (NGS) | Comprehensive analysis of genetic material | Identifying cancer-driving mutations and biomarkers 4 |
| Circulating Tumor DNA (ctDNA) Analysis | Detection of tumor-derived DNA in blood | Monitoring treatment response and minimal residual disease 6 |
| Artificial Intelligence Algorithms | Pattern recognition in complex datasets | Diagnostic accuracy, treatment prediction, and clinical trial optimization 4 |
| Spatial Transcriptomics | Gene expression analysis within tissue context | Understanding tumor microenvironment and treatment resistance 6 |
| Biomolecular Condensation Assays | Study of membraneless organelle formation | Investigating novel cancer mechanisms and potential therapeutic targets |
| Flow Cytometry | Analysis of physical and chemical characteristics of cells | Immunophenotyping and monitoring immune responses 4 |
While the landscape of cancer research publications may shift, the mission of institutions like A.C. Camargo Cancer Center continues to drive progress. Their integrated model—combining diagnosis, treatment, education, and research—represents an advanced approach to oncology 7 .
At A.C. Camargo, patients "are initially evaluated by a multidisciplinary group of specialists and then pass through an integrated process of care, from diagnosis to rehabilitation" 7 .
Despite these exciting advances, researchers acknowledge significant challenges:
As we've seen, the 'new phase' in cancer research extends far beyond the transition of a single journal. It encompasses transformative developments in precision medicine, artificial intelligence, and immunotherapy that are collectively reshaping how we understand and treat cancer.
"The launch of POI-2 marks a pivotal step in realising our collective strategic vision to advance precision medicine, accelerate interdisciplinary collaboration, and harness the transformative power of AI and digital technologies"
While the road ahead remains long, the convergence of these multiple 'new phases' in cancer research offers unprecedented hope. Through continued innovation, collaboration, and patient-centered care, the global research community moves closer to a future where cancer's burden is significantly reduced for all people.