Latest Research
All publications from the Cancer3.AI database, newest first.
Organ-specific inflammatory profiles during sepsis: divergent macrophage polarization and oxidative stress response in lung and liver in mouse model of caecal ligation and puncture.
Bodin A, et al
Researchers investigated how sepsis — a life-threatening systemic infection — triggers different inflammatory responses in the lungs and liver using the caecal ligation and puncture (CLP) mouse model, which closely mimics human sepsis. The study focused on macrophage polarization, a process by which immune cells shift toward either a pro-inflammatory (M1) or anti-inflammatory (M2) state, and examined oxidative stress markers in both organs. The findings revealed that the lung and liver mount distinct, organ-specific inflammatory and oxidative stress responses during sepsis, rather than a uniform systemic reaction. This divergence in macrophage behavior and oxidative damage suggests that therapeutic strategies targeting inflammation in sepsis may need to be tailored to individual organs rather than applied as a one-size-fits-all approach. These insights advance our understanding of sepsis-induced multi-organ dysfunction and may help guide the development of more precise, organ-targeted treatments for critically ill patients.
Journal of inflammation (London, England)
Source →Application of artificial intelligence in lung cancer diagnosis, therapy, and prognosis.
Wang J, et al
A new review published in BMC Medical Genomics examines how artificial intelligence is being applied across the full spectrum of lung cancer care, from early detection and diagnosis to treatment planning and outcome prediction. Lung cancer remains one of the deadliest cancers worldwide, and timely, accurate diagnosis is critical to improving survival rates. The review synthesizes recent advances in AI-based tools, including machine learning and deep learning algorithms, that analyze medical imaging, genomic data, and clinical records to assist clinicians in identifying tumors earlier and more accurately than traditional methods alone. These AI systems have demonstrated promising performance in tasks such as nodule detection on CT scans, pathological classification, and predicting patient responses to therapies. The authors highlight that integrating AI into clinical workflows could reduce diagnostic errors, personalize treatment strategies, and ultimately improve patient outcomes. This work underscores the growing importance of AI as a transformative tool in oncology and calls for further validation studies before widespread clinical adoption.
BMC medical genomics
Source →Hospital-to-home transitions of patients with lung cancer - a qualitative study of primary healthcare professionals' experiences.
Nilsen C, et al
A Norwegian qualitative study explored how general practitioners (GPs) and registered nurses (RNs) working in home care experience the transition of lung cancer patients from hospital to home. Researchers conducted focus group interviews, dyadic interviews, and one in-depth interview with five GPs and 16 RNs across three municipalities, using an inductive thematic analysis. The findings revealed that primary care professionals and hospital-based specialists operate under fundamentally different 'logics of care': hospital staff prioritized diagnosis and treatment, while home care nurses emphasized quality of life and patient preferences. A major barrier identified was the delayed and insufficient flow of health information from specialized care to primary care, leaving GPs and RNs without the details needed to safely continue patient care at home. When patients deteriorated, the lack of timely medical support from GPs frequently led nurses to re-hospitalize patients rather than manage their care in the community. The authors conclude that improved communication, face-to-face meetings, and interdisciplinary collaboration between hospital and primary care teams are essential to ensure safe, high-quality transitions for this vulnerable patient group.
BMC nursing
Source →Sex influences on tumor innervation.
Barclay SM, et al
Researchers investigated whether biological sex affects how tumors are infiltrated by nerves, studying oral cancers and melanoma in mouse models. They found that tumors grew more slowly in female mice and were more densely innervated than in males, though behavioral declines linked to a tumor-brain neural circuit did not differ significantly between sexes. When tumors were treated with cisplatin and radiation, tumor growth slowed in both sexes, but females showed significantly greater nerve infiltration and, critically, higher rates of lung metastasis compared to treated males. The study also revealed that tumors activate neurons and glial cells in brain projection areas, and that standard-of-care treatment reduces this activation, which correlates with improved behavior in tumor-bearing animals. These findings highlight that sex is an important biological variable in tumor neuroscience and suggest that targeting or silencing the tumor-brain neural circuit could open new avenues for improving cancer treatment outcomes in both men and women.
Biology of sex differences
Source →TUSC7 expression and mutational profile define its potential as a diagnostic and therapeutic biomarker in non-small cell lung cancer.
Martin-Lopez P, et al
Researchers investigated the long non-coding RNA TUSC7 (Tumor Suppressor Candidate 7) as a potential diagnostic and therapeutic biomarker in non-small cell lung cancer (NSCLC), the most common form of lung cancer worldwide. The study characterized TUSC7 expression levels across NSCLC patient samples and catalogued the mutational landscape of the gene to understand how alterations in TUSC7 relate to cancer development and progression. Findings revealed that TUSC7 expression is significantly dysregulated in NSCLC tumors compared to normal lung tissue, and that specific mutational patterns correlate with distinct clinical outcomes. These results suggest that TUSC7 could serve as a reliable molecular marker for earlier and more accurate diagnosis of NSCLC, as well as a potential target for novel therapeutic strategies. For patients, this research opens the door to more personalized treatment approaches based on the molecular profile of their tumor.
Biomarker research
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