Preoperative chemoradiotherapy (PCRT) and subsequent surgery is the standard multimodal treatment for locally advanced rectal cancer (LARC), albeit PCRT response varies among the individuals. This creates a dire necessity to identify a predictive model to forecast treatment response outcomes and identify patients who would benefit from PCRT. In this study, we performed a gene expression study using formalin-fixed paraffin-embedded (FFPE) tumor biopsy samples from 156 LARC patients (training cohort n = 60; validation cohort n = 96); we identified the nine-gene signature (FGFR3, GNA11, H3F3A, IL12A, IL1R1, IL2RB, NKD1, SGK2, and SPRY2) that distinctively differentiated responders from non-responders in the training cohort (accuracy = 86.9%, specificity = 84.8%, sensitivity = 81.5%) as well as in an independent validation cohort (accuracy = 81.0%, specificity = 79.4%, sensitivity = 82.3%). The signature was independent of all pathological and clinical features and was robust in predicting PCRT response. It is readily applicable to the clinical setting using FFPE samples and Food and Drug Administration (FDA) approved hardware and reagents. Predicting the response to PCRT may aid in tailored therapies for respective responders to PCRT and improve the oncologic outcomes for LARC patients.

Our findings collectively demonstrate that preoperative TACE confers poor prognosis in HCC patients through activation of HIF-1α.

<b><i>Background/Aim:</i></b> Uniform treatment of hepatocellular carcinoma (HCC) with molecular targeted drugs (e.g., sorafenib) results in a poor overall tumor response when tumor subtyping is absent. Patient stratification based on actionable gene expression is a method that can potentially improve the effectiveness of these drugs. Here we aimed to identify the clinical application of actionable genes in predicting response to sorafenib. <b><i>Methods:</i></b> Through quantitative real-time reverse transcription PCR, we analyzed the expression levels of seven actionable genes (<i>VEGFR2</i>, <i>PDGFRB</i>, <i>c-KIT</i>, <i>c-RAF</i>, <i>EGFR</i>, <i>mTOR</i>, and <i>FGFR1</i>) in tumors versus noncancerous tissues from 220 HCC patients treated with sorafenib. Our analysis found that 9 responders did not have unique clinical features compared to nonresponders. A receiver operating characteristic curve evaluated the predictive performance of the treatment benefit score (TBS) calculated from the actionable genes. <b><i>Results:</i></b> The responders had significantly higher TBS values than the nonresponders. With an area under the curve of 0.779, a TBS combining <i>mTOR</i> with <i>VEGFR2</i>, <i>c-KIT</i>, and <i>c-RAF</i> was the most significant predictor of response to sorafenib. When used alone, sorafenib had a 0.7–3% response rate among HCC patients, but when stratifying the patients with actionable genes, the tumor response rate rose to 15.6%. Furthermore, actionable gene expression is significantly correlated with tumor response. <b><i>Conclusions:</i></b> Our findings on patient stratification based on actionable molecular subtyping potentially provide a therapeutic strategy for improving sorafenib’s effectiveness in treating HCC.

BackgroundThe effectiveness of molecular targeted agents is modest in hepatocellular carcinoma (HCC). Efficacy of molecular targeted therapies has been better in cancer patients with high expression of actionable molecules defined as cognate target molecules. However, patient stratification based on the actionable molecules dictating the effectiveness of targeted drugs has remained understudied in HCC.Experimental Design & ResultsPaired tumor and non-tumoral tissues derived from a total of 130 HCC patients were studied. Real-time RT-PCR was used to analyze the mRNA expression of actionable molecules in the tissues. mRNA levels of EGFR, VEGFR2, PDGFRβ, FGFR1, and mTOR were up-regulated in tumors compared to non-tumors in 35.4, 42.3, 61.5, 24.6, and 50.0% of patients, respectively. Up-regulation of EGFR was observed at early stage and tended to gradually decrease toward late stages (BCLC stage A: 41.9%; B: 30.8%; C: 17.6%). Frequency of VEGFR2 expression in tumors at stage C was lower than that in the other stages (BCLC stage A: 45.9%; B: 41.0%; C: 29.4%). PDGFRβ and mTOR were observed to be up-regulated in more than 50% of tumors in all the stages whereas FGFR1 was up-regulated in only about 20% of HCC irrespective of stages. A cluster analysis of actionable gene expression revealed that HCC can be categorized into different subtypes that predict the effectiveness of molecular targeted agents and combination therapies in clinical trials. Analysis of in vitro sensitivity to sorafenib demonstrated that HCC cells with up-regulation of PDGFRβ and c-Raf mRNA are more susceptible to sorafenib treatment in a dose and time-dependent manner than cells with low expression of the genes.ConclusionsmRNA expression analysis of actionable molecules could provide the rationale for new companion diagnostics-based therapeutic strategies in the treatment of HCC.