Medical Bulletin 12/ February/ 2025

A research team has developed a gastric cancer model using 3D bioprinting technology and patient-derived cancer tissue fragments. This innovative model preserves the characteristics of actual patient tissues and is expected to rapidly evaluate and predict individual patient drug responses. The research has been published in the international journal Advanced Science.

In this study, the research team developed an in vitro gastric cancer model by leveraging 3D bioprinting technology and tissue-specific bioink incorporating patient-derived tissue fragments.

Notably, they encapsulated cancer tissues within a stomach-derived decellularized extracellular matrix (dECM) hydrogel, artificially enabling cell-matrix interactions. By co-culturing these tissues with human gastric fibroblasts, they successfully mimicked cancer cell-stroma interactions, thereby recreating the in vivo tumor microenvironment in vitro.

This model demonstrated the ability to preserve the unique characteristics of gastric tissues from individual patients by replicating both cell-stroma and cell-matrix interactions. It exhibited high specificity in predicting the patient's anticancer drug responses and prognosis. Furthermore, the model's gene profiles related to cancer development, progression, and drug response closely resembled those of patient tissues, surpassing the performance of conventional PDX models.

Additionally, the rapid fabrication method of this model via bioprinting enables drug evaluation within two weeks of tumor tissue extraction from the patient. This efficient platform is anticipated to significantly contribute to the development of personalized cancer treatments.

Professor Charles Lee from The Jackson Laboratory for Genomic Medicine, who led the study, expressed his expectations for the model: "By reproducing cancer cell-stroma and cell-matrix interactions, this model enhances the accuracy of drug response predictions and reduces unnecessary drug administration to non-responsive patients."

Reference: Y. Choi, D. Na, G. Yoon, J. Kim, S. Min, H.-G. Yi, S.-J. Cho, J. H. Cho, C. Lee, J. Jang, Prediction of Patient Drug Response via 3D Bioprinted Gastric Cancer Model Utilized Patient-Derived Tissue Laden Tissue-Specific Bioink. Adv. Sci. 2024, 2411769. https://doi.org/10.1002/advs.202411769

A new study Published in eBioMedicine research has identified genetic overlaps in 72 long-term health conditions associated with aging, to identify where specific genes are linked to two or more conditions.

The study analysed millions of both genetic and patient records on the long-term health conditions of later life and has identified opportunities for new ways to prevent and treat multiple overlapping conditions. The GEMINI study looked at both genetics and clinical information from more than three million people in the UK and Spain.

With more than 2,500 combinations of conditions analysed, the programme aims to unlock cases where a drug or prevention strategies can prevent or delay the onset of multimorbidity. It also revealed genetic connections that explain why certain conditions may be more likely to co-occur in the same patient.

Dr Joao Delgado, at the University of Exeter Medical School led the research.

He said: "Overlapping long-term conditions have a huge impact on the lives of millions of people and are difficult and costly to treat. For the first time, we've combined analysis of both genetics and clinical records on a massive scale, in a new and robust approach to identify where genes play a critical role in more than one condition. We're now working to drill down into specifics combination of conditions, and expect to reveal drugs or lifestyle changes that already work for treating existing conditions that can be repurposed to prevent multimorbidity, with promising results. For example, we identified the role of treatable conditions, such as B12 deficiency and iron deficiency anaemia in the development of multimorbidity. This will lead to a more personalised approach to prevention and treatment in multimorbidity."

Reference:https://news.exeter.ac.uk/faculty-of-health-and-life-sciences/genetic-research-unlocks-new-ways-to-prevent-and-treat-multiple-long-term-conditions/

A new study which investigated how social media use impacts loneliness over time suggested that the very platforms designed to bring us together contribute to an "epidemic of loneliness."

The findings showed that both passive (PSMU) and active (ASMU) social media use were associated with increased feelings of loneliness over time. While passive social media use—like browsing without interaction—predictable lead to heightened loneliness, active use, involving posting and engaging with others, was also linked to increased feelings of loneliness. These results suggest that the quality of digital interactions may not fulfill the social needs that are met in face-to-face communication.

The findings emphasize an urgent need for further research into the effects of digital interaction, underlining the essential role of in-person connections in supporting well-being. This study adds a valuable perspective to the conversation on how digital habits influence mental health, offering insights to shape future mental health initiatives, policies, and guidelines for healthier social media use.

“This research underscores the complexity of social media’s impact on mental health,” said primary investigator James A. Roberts, Ph.D. “While social media offers unprecedented access to online communities, it appears that extensive use—whether active or passive—does not alleviate feelings of loneliness and may, in fact, intensify them.”

The study also found a two-way relationship between loneliness and social media use. "It appears that a continuous feedback loop exists between the two,” Roberts, Ph.D. “Lonely people turn to social media to address their feelings, but such social media may use merely fans the flames of loneliness."

Reference: Roberts, J. A., Young, P. D., & David, M. E. (2025). The Epidemic of Loneliness: A 9-Year Longitudinal Study of the Impact of Passive and Active Social Media Use on Loneliness. Personality and Social Psychology Bulletin, 0(0). https://doi.org/10.1177/01461672241295870