Breast cancer immunotherapy: a comprehensive review

Current Non-Surgical Curative Regenerative Therapies for Knee Osteoarthritis

Osteoarthritis (OA) is a prevalent musculoskeletal disease affecting middle-aged and elderly individuals, with knee pain as a common complaint. Standard therapy approaches generally attempt to alleviate pain and inflammation, using various pharmacological and non-pharmacological options. However, the efficacy of these therapies in long-term tissue repair remains debated. As an alternative, regenerative medicine offers a promising strategy, with decreased adverse event rates and increasing evidence of safety and efficacy. This review will outline current advances in regenerative medicine for knee OA, emphasizing outpatient clinic-based therapies that use orthobiological and non-biological products. Different strategies based on orthobiologics are discussed as potential regenerative options for the management of knee OA. Cell-free therapies including platelet-rich plasma, autologous anti-inflammatories, exosomes, human placenta extract, and mitochondrial transplantation are discussed, focusing on their potential for cartilage regeneration. Additionally, cell-based therapies with regenerative properties including bone marrow aspirate concentrate, adipose stromal vascular fraction, microfat, nanofat, stem cell therapy, and genetically modified cells as part of orthobiologics, are being investigated. Also, this study is looking into non-biological approaches such as using gold-induced cytokines, extracorporeal shockwave therapy, and ozone therapy. The mechanisms of action, effectiveness, and clinical applications of each therapy are being explored, providing insights into their role in the management of knee OA.

From Biosensors to Robotics: Pioneering Advances in Breast Cancer Management

Breast cancer stands as the most prevalent form of cancer amongst females, constituting more than one-third of all cancer cases affecting women. It causes aberrant cell development, which can assault or spread to other sections of the body, perhaps leading to the patient's death. Based on research findings, timely detection can diminish the likelihood of mortality and enhance the quality of healthcare provided for the illness. However, current technologies can only identify cancer at an advanced stage. Consequently, there is a substantial demand for rapid and productive approaches to detecting breast cancer. Researchers are actively pursuing precise and timely methods for the diagnosis of breast cancer, aiming to achieve enhanced accuracy and early detection. Biosensor technology can allow for the speedy and accurate diagnosis of cancer-related cells, as well as a more sensitive and specialized technique for generating them. Additionally, numerous treatments for breast cancer are depicted such as herbal therapy, nanomaterial-based drug delivery, miRNA targeting, CRISPR technology, immunotherapy, and precision medicine. Early detection and efficient therapy are necessary to manage such a severe illness properly.

Senescent cell-derived vaccines: a new concept towards an immune response against cancer and aging?

Two recent seminal works have untangled the intricate role of tumor-associated senescent cells in cancer progression, or regression, by guiding our immune system against cancer cells. The characterization of these unique, yet diverse cell populations, should be considered, particularly when contemplating the use of senolytics, which are drugs that selectively eliminate senescent cells, in a cancer framework. Here, we will describe the current knowledge in this field. In particular, we will discuss how the presence of senescent cells in tumors could be used as a therapeutic target in immunogenic cancers and how we may hypothetically design an adaptive anti-aging vaccine.

A new 4-gene-based prognostic model accurately predicts breast cancer prognosis and immunotherapy response by integrating WGCNA and bioinformatics analysis

Background

Breast cancer (BRCA) is a common malignancy in women, and its resistance to immunotherapy is a major challenge. Abnormal expression of genes is important in the occurrence and development of BRCA and may also affect the prognosis of patients. Although many BRCA prognosis model scores have been developed, they are only applicable to a limited number of disease subtypes. Our goal is to develop a new prognostic score that is more accurate and applicable to a wider range of BRCA patients.

Methods

BRCA patient data from The Cancer Genome Atlas database was used to identify breast cancer-related genes (BRGs). Differential expression analysis of BRGs was performed using the 'limma' package in R. Prognostic BRGs were identified using co-expression and univariate Cox analysis. A predictive model of four BRGs was established using Cox regression and the LASSO algorithm. Model performance was evaluated using K-M survival and receiver operating characteristic curve analysis. The predictive ability of the signature in immune microenvironment and immunotherapy was investigated. In vitro experiments validated POLQ function.

Results

Our study identified a four-BRG prognostic signature that outperformed conventional clinicopathological characteristics in predicting survival outcomes in BRCA patients. The signature effectively stratified BRCA patients into high- and low-risk groups and showed potential in predicting the response to immunotherapy. Notably, significant differences were observed in immune cell abundance between the two groups. In vitro experiments demonstrated that POLQ knockdown significantly reduced the viability, proliferation, and invasion capacity of MDA-MB-231 or HCC1806 cells.

Conclusion

Our 4-BRG signature has the potential as an independent biomarker for predicting prognosis and treatment response in BRCA patients, complementing existing clinicopathological characteristics.