A Riskscore Model for Predicting Survival, Tumor Microenvironment, Immunotherapy and drug sensitivity of Lung Squamous Cell Carcinoma Based on PI3K/AKT/MTOR Pathway-Related Genes

<p>Firstly, the data we provide is the raw data downloaded from the TCGA database. Secondly, we provide the following explanations for the raw data, taking Figure 1 as an example:</p> <p>First, we selected a LUSC dataset from the TCGA database that includes RNA-seq data (FPKM values) and clear clinical information, consisting of 51 normal samples and 501 LUSC samples. The raw data <span>can be found in</span>&nbsp;the "mRNA" document in the "Fig.1" file<span>, and t</span>he data includes TCGA <span>id</span>&nbsp;information.</p> <p>Next, the data was imported into "mRNA_edgeR" to analyze whether the RNA-seq data from these 552 samples meet the criteria of |logFC| &gt; 0.585 and FDR &lt; 0.05, <span>and the results are shown in</span>&nbsp;the "diffSig" table. Subsequently, the genes in the "diffSig" table were intersected with 105 PAGs,&nbsp;<span>and</span>&nbsp;44 key PAGs <span>were identified, </span>as shown in Figure 1.</p> <p>The <span>other</span>&nbsp;figures can <span>also </span>be reproduced sequentially based on the methods described <span>above</span>.</p> <p>Furthermore, due to the limited number of LUSC patients, the clinical information in the database is relatively incomplete. Hence, the clinical information that we provide constitutes the entire content available in the database.</p>