Hydroxylated Cyclopamine Analogues from Veratrum californicum and Their Hedgehog Pathway Inhibiting Activity

Nonsurgical therapy for lumbar spinal stenosis caused by ligamentum flavum hypertrophy: A review

Lumbar spinal stenosis (LSS) can cause a range of cauda equina symptoms, including lower back and leg pain, numbness, and intermittent claudication. This disease affects approximately 103 million people worldwide, particularly the elderly, and can seriously compromise their health and well-being. Ligamentum flavum hypertrophy (LFH) is one of the main contributing factors to this disease. Surgical treatment is currently recommended for LSS caused by LFH. For patients who do not meet the criteria for surgery, symptom relief can be achieved by using oral nonsteroidal anti-inflammatory drugs (NSAIDs) and epidural steroid injections. Exercise therapy and needle knife can also help to reduce the effects of mechanical stress. However, the effectiveness of these methods varies, and targeting the delay in LF hypertrophy is challenging. Therefore, further research and development of new drugs is necessary to address this issue. Several new drugs, including cyclopamine and N-acetyl-l-cysteine, are currently undergoing testing and may serve as new treatments for LSS caused by LFH.

Classification of molecular subtypes for colorectal cancer and development of a prognostic model based on necroptosis-related genes

Background

Necroptosis could regulate immunity in cancers, and stratification of colorectal cancer (CRC) subtypes based on key genes related to necroptosis might be a novel strategy for CRC treatment.

Method

The RNA-sequencing data of CRC and other 31 types of cancers were obtained from The Cancer Genome Atlas (TCGA) database. Consensus clustering was performed based on protein-coding genes (PCGs) related to necroptosis score calculated by single sample gene set enrichment analysis (ssGSEA). Module genes showing a significant positive correlation with the necroptosis score were identified by weighted correlation network analysis (WGCNA) and further used to develop a risk stratification model applying least absolute shrinkage and selection operator (LASSO) and Cox regression analysis. The risks score for each sample in CRC cohorts, immunotherapy cohorts and pan-cancer study cohorts was calculated.

Result

Two subgroups (C1 cluster and C2 cluster) of CRC were identified based on the necroptosis score. Compared with C1 cluster, the survival possibility of C2 cluster was greatly reduced, the levels of necroptosis score, immune cell infiltration, immune score and expression of immune checkpoint molecules were significantly increased and immunotherapy response was less active. Low-risk patients defined by the risk model had a significant survival advantage than high-risk counterparts in both CRC and the other 31 cancer types. Furthermore, the risk model was also more efficient than the Tumor Immune Dysfunction and Exclusion (TIDE) tool in predicting OS and immunotherapy response for the samples in the immunotherapy cohort.

Conclusion

CRC patients were classified by necroptosis score-related PCGs, and a risk model was designed to evaluate the immunotherapy and prognosis of patients with CRC. The current molecular subtype and prognostic model could help stratify patients with different risks and predict their prognosis and immunotherapy sensitivity.