Results of study led by investigators at the Vall d'Hebron Institute of Oncology (VHIO) show convergent genetic adaptation under hypoxia (lack of oxygen) between populations living at high-altitude in the Himalayan region such as Tibetans and Sherpas, and the development of oxygen-starved cancer cells.

In recent years, chemotherapy-induced cardiovascular disease has emerged as a significant cause of mortality among cancer survivors. Anthracyclines, pivotal in treating cancers like breast cancer and leukemia, are indispensable in cancer therapy, yet their severe cardiotoxicity presents a formidable challenge. A recent review in Medicine Plus offers profound insights into anthracycline-induced cardiotoxicity (AIC), exploring its mechanisms and therapeutic strategies, contributing to safer oncological treatments in the future.

Recently, Pingping Zhu, Zhenzhen Chen, Qiankun He from Zhengzhou University and Xinrui Lv from Henan University published a review paper on MedComm-Oncology, which is titled "Characteristic, Regulation and Targeting Strategies of Cancer Stem Cells and Their Niche in Digestive System Tumors". They comprehensively reviewed the recent progress in understanding and targeting of CSCs and their niche.

For the first time, researchers have revealed the high-affinity interaction between mitochondrial proteins HAX1 (intrinsically disordered) and CLPB (α-helical), uncovering their structural and functional synergy. Using NMR, the study shows HAX1's disordered region binds CLPB's helical domain with low micromolar affinity, providing mechanistic insights into diseases like cancer and mitochondrial encephalomyopathy. These findings open new avenues for targeted therapies against mitochondrial dysfunction-related disorders.

This work developed a new deep learning framework, MULGONET, to predict cancer recurrence and identify key biomarkers by integrating multi omics data (such as mRNA, DNA methylation, copy number variation). By utilizing the gene ontology (go) hierarchy, the model overcomes the challenges of data dimensionality and interpretability, and achieves higher accuracy in bladder cancer, pancreatic cancer, and gastric cancer datasets. This innovation enables clinicians to pinpoint key genes and biological pathways associated with cancer recurrence, paving the way for personalized treatment strategies.