Mammography, a cornerstone of cancer detection, employs low-dose X-rays to examine breast tissue for abnormalities. Its efficacy in detecting early-stage breast cancer is well-established, significantly enhancing survival rates. However, challenges persist, notably false positives leading to unnecessary anxiety and interventions, and false negatives potentially delaying treatment. Advanced technologies like digital mammography and 3D tomosynthesis offer improved accuracy, particularly in dense breast tissue. Additionally, emerging AI algorithms aid in interpreting mammograms, augmenting radiologists' expertise. Despite these advancements, accessibility and adherence to screening remain barriers, especially in underserved communities. Continued research focuses on refining screening protocols, integrating AI further, and exploring adjunctive techniques like molecular imaging for more precise diagnoses, striving towards more effective breast cancer detection and management.
Title : A novel blood-based mRNA genomics technology for cancer diagnosis and treatment
Rajvir Dahiya, University of California San Francisco, United States
Title : tRNA-derived fragment 3′tRF-AlaAGC modulates cell chemoresistance and M2 macrophage polarization via binding to TRADD in breast cancer
Feng Yan, The Affiliated Cancer Hospital of Nanjing Medical University, China
Title : Integrating single-cell and spatial transcriptomics to uncover and elucidate GP73-mediated pro-angiogenic regulatory networks in hepatocellular carcinoma
Jiazhou Ye, Guangxi Medical University Cancer Hospital, China
Title : Unveiling the synergism of radiofrequency therapy and graphene nanocomposite in tumor cell viability assay
Paulo Cesar De Morais, Catholic University of Brasilia, Brazil
Title : Analysis of the dynamic evolution and influencing factors of nutritional risk in breast cancer patients during treatment
Jingwen Yan, Sun Yat-sen University, China
Title : Integrative multi-omics reveals metabolic–stemness coupling and novel therapeutic targets in osteosarcoma chemoresistance
Jinyan Feng, Tianjin Medical University Cancer Institute and Hospital, China