Life science
Medical & healthcare, Drug development

Prediction of therapeutic effect of combined immunotherapy using tumor microenvironment
analysis and MRI images of hepatocellular carcinoma
Department of Gastroenterology and Hepatology, Graduate School of Medicine
Assistant Professor Takahiro Kodama

https://researchmap.jp/takahirokodama?lang=en

Professor Tetsuo Takehara				https://researchmap.jp/takeharatetsuo?lang=en

Life science

Abstract
Hepatocellular carcinoma (HCC) is known as a cancer with ahigh recurrence rate and poor prognosis. Pharmacotherapy suchas anti-PD-L1 antibody/anti-VEGF antibody combination immunotherapy (atezolizumab/bevacizumab) becomes applicable to advanced HCC, but its efficacy is limited. Therefore, there is a needfor biomarkers that can predict the therapeutic efficacy of eachdrug. In this study, we performed a multi-omics analysis using
resected specimens from over 100 HCC patients and found thatsteatotic HCC, which is characterized by fat droplet accumulation
within cancer cells, is in a state of immune exhaustion that is more
likely to benefit from immune checkpoint inhibitors. We showed thatsteatotic HCC patients identified by MRI images have a better response to combination immunotherapy.

Figure 1▍ Background & Results
According to WHO statistics, liver cancer is the third most common cancer in terms of deaths (approximately 830,000). In Japan,
the annual number of deaths reaches 25,000, and the five-year
survival rate is reported to be 35.8%. In recent years, a variety ofdrugs have been developed to treat advanced cases, and a totalof eight treatment options exist, centered on the first-line anti-PD-L1
antibody/anti-VEGF antibody combination immunotherapy (atezolizumab/bevacizumab). On the other hand, the problem is thatless than 30% of patients achieve tumor disappearance/reduction
with any of these therapies. Therefore, “personalized medicine,” inwhich the most appropriate drug is selected for each patient, is important to improve prognosis, and the development of biomarkers
to predict therapeutic efficacy of each drug is an urgent issue. We
performed transcriptomic and genomic analyses using resected
HCC tissues from 113 patients. We analyzed the tumor immune
microenvironment and examined the relationship with clinicopathological factors. As a result, we found that steatotic HCC, in whichcancer cells have fat droplet accumulation, shows strong immune
cell infiltration in the tumor, while the infiltrated immune cells areexhausted. Lipidomic analysis identified that palmitic acid, a typeof saturated fatty acid, increased in steatotic HCC. Furthermore,
we found that palmitic acid increases the expression of PD-L1 on
the membrane surface of HCC cells. Finally, we have shown thatsteatotic HCC can be identified by MRI imaging and are highly
sensitive to atezolizumab-bevacizumab combination therapy.

Figure 2▍ Significance of the research and Future perspective
By predicting the therapeutic effect of combined immunotherapy
in advance, it is expected to contribute to improving the prognosisof patients with advanced HCC by enabling more optimal drug
selection among various drug therapy options. In addition, since
MRI is performed for the diagnosis of HCC, it is expected to be apatient-friendly noninvasive biomarker. Furthermore, this study isexpected to lead to the development of therapeutic agents targeting the immune escape mechanism of HCC via fat droplet accumulation.

Figure 3

P a t e n t PCT/JP2023/016673
Murai, Hiroki; Kodama, Takahiro; Maesaka, Kazuki et al. Multiomics identifies the link between intratumor steatosis and the exhausted tumor immune
Tr e a t i s e
microenvironment in hepatocellular carcinoma. Hepatology 2023, 77(1), 77-91. doi: 10.1002/hep.32573
URL
K e y w o r d steatotic HCC, immune exhaustion, immune checkpoint inhibitor, MRI, biomarker