A 10-Gene Signature Identified by Machine Learning for Predicting the Response to Transarterial Chemoembolization in Patients with Hepatocellular Carcinoma

<div>TILs and tumor stemness comparison between response and nonresponse groups. (a) Violin plot displaying 22 TILs distribution using CIBERSORTx algorithm between the given TACE responders and nonresponders in GSE104580. (b) Comparison of 22 TILs fraction in predicted responders and nonresponders in GSE104580 with our devised model. (c) Comparison of 22 TILs fraction in predicted responders and nonresponders in GSE14520 with our devised model. (d) Tumor stemness index between given TACE responders and nonresponders in GSE104580. (e) Tumor stemness index of predicted response and nonresponse patients in GSE104580 using our model. (f) Tumor stemness index of predicted response and nonresponse group in GSE14520 using our model.</div>

Journal of Oncology

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Figure 6: A 10-Gene Signature Identified by Machine Learning for Predicting the Response to Transarterial Chemoembolization in Patients with Hepatocellular Carcinoma 

Figure 6 | A 10-Gene Signature Identified by Machine Learning for Predicting the Response to Transarterial Chemoembolization in Patients with Hepatocellular Carcinoma 