Editor’s Note: At the 2024 European Society for Medical Oncology (ESMO) Annual Meeting, in the session dedicated to basic science and translational research, researchers presented groundbreaking findings on driver mutations in pancreatic cancer and their role in predicting patient prognosis and treatment response. The research highlighted significant differences in the diversity of driver gene mutations between healthy pancreatic tissue and tumor tissue, suggesting these differences play a crucial role in the formation and progression of pancreatic cancer. These findings also provide an important basis for personalized treatment. Dr. Francisco Martínez-Jiménez from Vall d'Hebron Barcelona Hospital Campus , Spain, interpreted the main research findings and discussed their clinical implications.

Driver Mutations Reveal the Diverse Mechanisms of Pancreatic Cancer Development

At ESMO 2024, research teams from the UK, the Netherlands, and Spain presented a comprehensive analysis of healthy pancreatic tissue and tumor tissue, revealing striking differences in the driver mutations between the two. This study analyzed 181 pancreatic samples from 118 healthy donors and 62 tumor tissue samples from 4 patients with pancreatic ductal adenocarcinoma (PDAC) using laser capture microdissection, whole-exome sequencing, and NanoSeq technologies to systematically characterize somatic mutations in the samples.

The results showed that the mutation burden in healthy pancreatic tissue was significantly lower than in tumor tissue. In healthy donors, only 0.81% to 3.6% of cells carried driver mutations, primarily involving genes like APC and PRSS1. In contrast, 45% to 64% of untreated PDAC patient cells carried driver mutations, mainly in the KRAS and TP53 genes (see Figure 1). Additionally, in 16 samples from 9 donors, researchers identified sporadic pre-cancerous lesions with KRAS driver mutations.

This analysis of the somatic mutation spectrum across different pancreatic cancer tissue samples helps uncover the early molecular events and evolutionary processes involved in cancer development. Future studies will further explore the interaction mechanisms between these driver gene mutations and other environmental factors, aiding in the identification of high-risk populations for pancreatic cancer. This will support the development of early diagnosis and prevention strategies. Moreover, this research has important implications for the advancement of precision medicine, promoting the further development of personalized treatment strategies for pancreatic cancer and offering patients more effective treatment options. By integrating molecular biology with clinical data, there is hope for more precise risk assessment and treatment selection in the future.

Functional Models to Predict Treatment Response in Pancreatic Cancer Patients

In another study, researchers integrated molecular and clinical variables into patient-derived organoid (PDO) functional screening, significantly enhancing the ability to predict specific treatment responses in pancreatic cancer patients. The research team collected 155 PDO samples from 70 pancreatic cancer patients and 85 colorectal cancer patients, simulating drug responses observed in clinical treatments to evaluate how each PDO responded to different therapies. This method allowed researchers to more accurately predict how patients would respond in real clinical settings, providing a more reliable basis for personalized treatment.

Based on these data, the researchers developed a prospective patient response prediction model that combines biochemical endpoint detection with multimodal analysis to comprehensively assess PDO treatment responses. The results showed that this model effectively predicted overall treatment response and progression-free survival (PFS) in patients with complete clinical outcome data. Further analysis indicated that when molecular and clinical variables, such as the number of treatment lines and disease type, were incorporated into the predictive model, the accuracy of the predictions significantly improved. After controlling for clinical and molecular variables, the predictive value of PDO functional screening was enhanced (HR: 4.36; P=0.0027; 95%CI: 1.66~11.41). This finding underscores the potential role of patient-specific testing in precision medicine.

This study not only highlights the potential of PDO functional screening in predicting treatment response but also provides new tools and insights for the development of future personalized treatments. By accurately predicting individual patient responses, clinicians can make more informed decisions on the most appropriate treatment plans, thereby significantly improving patient outcomes. This advancement will further drive the application of precision medicine in pancreatic cancer treatment, supporting more effective clinical decision-making and laying a strong foundation for the development of personalized treatment strategies.

Clinical Significance and Future Outlook

“These studies emphasize the diversity of driver mutations and the significant impact of clinical and molecular factors on tumor progression and patient prognosis,” explained Dr. Francisco Martínez-Jiménez from Vall d’Hebron Hospital in Barcelona. “In PDAC, KRAS and TP53 are the most common driver mutations, often found in pre-cancerous lesions such as pancreatic intraepithelial neoplasia and other malignancies. In contrast, although mutations in other genes may also occur in healthy pancreatic tissue, these mutations are often only selectively favored in a small range of cells (i.e., ‘positive selection’), meaning that cells carrying these mutations may have a growth advantage in localized tissue but are not sufficient to cause cancerous transformation. This phenomenon suggests that KRAS and TP53 possess unique ‘transformative potential,’ while other positively selected gene mutations in healthy pancreatic tissue may lack the capacity to trigger cancer development.”

Researchers noted that although driver gene mutations are essential for cancer initiation, these mutations alone are often insufficient to cause cancer. This finding highlights the crucial role of environmental factors in the selection and transformation process of pancreatic cancer, such as chronic inflammation, changes in the tumor microenvironment, or prolonged exposure to external carcinogens. Thus, cancer development is not the result of a single factor but rather a complex interaction of multiple internal and external factors. This study not only deepens our understanding of the early mechanisms of pancreatic cancer but also provides a new perspective and foundation for the development of personalized treatment strategies. It aids in identifying potential intervention targets and high-risk populations, thereby promoting the application of precision medicine in pancreatic cancer treatment.

These studies have deepened our understanding of the role of driver genes in pancreatic cancer and revealed their important value in predicting treatment response and survival outcomes. By integrating molecular biology with clinical data, we can more accurately predict individual treatment outcomes, providing a new scientific basis for personalized treatment strategies in pancreatic cancer. As research continues to evolve, we will further unravel the mechanisms of pancreatic cancer driver genes and accelerate the application of precision medicine in its treatment. Researchers hope to make breakthroughs in early diagnosis, therapeutic target discovery, and prognosis evaluation, ultimately improving patient survival and advancing the development of precision medicine in pancreatic cancer.