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Distinct tumor microenvironment landscapes of rectal cancer for prognosis and prediction of immunotherapy response - PubMed
Source: pubmed.ncbi.nlm.nih.gov
Article summary:
1. This article presents a comprehensive analysis of the tumor microenvironment (TME) landscape of rectal cancer, including both immune and non-immune components.
2. The authors proposed a subtyping strategy based on the abundance of TME elements, which divided all RC patients into 4 subtypes.
3. A 10-gene signature was constructed to predict prognosis and immunotherapy response, and a nomogram was established in combination with M stage and age to provide an accurate prediction of prognosis.
Article analysis:
The article is generally reliable and trustworthy as it provides a comprehensive analysis of the tumor microenvironment (TME) landscape of rectal cancer, including both immune and non-immune components. The authors proposed a subtyping strategy based on the abundance of TME elements, which divided all RC patients into 4 subtypes. Furthermore, they constructed a 10-gene signature to predict prognosis and immunotherapy response, and established a nomogram in combination with M stage and age to provide an accurate prediction of prognosis.
The article is well written with clear explanations for each step taken in the research process. The authors have provided sufficient evidence for their claims by using single-cell analysis, ssGSEA, hclust, WGCNA, LASSO regression, diverse machine learning algorithms etc., which makes their findings more reliable. Moreover, they have also validated their results in two GEO datasets to ensure accuracy.
There are no major biases or unsupported claims in this article as it is well researched and supported by evidence from various sources. However, there are some minor points that could be improved upon such as providing more detailed information about the machine learning algorithms used for survival prediction or exploring other possible factors that may affect prognosis or immunotherapy response such as lifestyle factors or genetic mutations.