High Throughput Transcriptome Data Analysis and Computational Verification Reveal Immunotherapy Biomarkers of Compound Kushen Injection for Treating Triple-Negative Breast Cancer

Abstract

BackgroundAlthough notable therapeutic and prognostic benefits of compound kushen injection (CKI) have been found when it was used alone or in combination with chemotherapy or radiotherapy for triple-negative breast cancer (TNBC) treatment, the effects of CKI on TNBC microenvironment remain largely unclear. This study aims to construct and validate a predictive immunotherapy signature of CKI on TNBC.MethodsThe UPLC-Q-TOF-MS technology was firstly used to investigate major constituents of CKI. RNA sequencing data of CKI-perturbed TNBC cells were analyzed to detect differential expression genes (DEGs), and the GSVA algorithm was applied to explore significantly changed pathways regulated by CKI. Additionally, the ssGSEA algorithm was used to quantify immune cell abundance in TNBC patients, and these patients were classified into distinct immune infiltration subgroups by unsupervised clustering. Then, prognosis-related genes were screened from DEGs among these subgroups and were further overlapped with the DEGs regulated by CKI. Finally, a predictive immunotherapy signature of CKI on TNBC was constructed based on the LASSO regression algorithm to predict mortality risks of TNBC patients, and the signature was also validated in another TNBC cohort.ResultsTwenty-three chemical components in CKI were identified by UPLC-Q-TOF-MS analysis. A total of 3692 DEGs were detected in CKI-treated versus control groups, and CKI significantly activated biological processes associated with activation of T, natural killer and natural killer T cells. Three immune cell infiltration subgroups with 1593 DEGs were identified in TNBC patients. Then, two genes that can be down-regulated by CKI with hazard ratio (HR) > 1 and 26 genes that can be up-regulated by CKI with HR < 1 were selected as key immune- and prognosis-related genes regulated by CKI. Lastly, a five-gene prognostic signature comprising two risky genes (MARVELD2 and DYNC2I2) that can be down-regulated by CKI and three protective genes (RASSF2, FERMT3 and RASSF5) that can be up-regulated by CKI was developed, and it showed a good performance in both training and test sets.ConclusionsThis study proposes a predictive immunotherapy signature of CKI on TNBC, which would provide more evidence for survival prediction and treatment guidance in TNBC as well as a paradigm for exploring immunotherapy biomarkers in compound medicines.

Single-cell RNA-sequencing uncovers compound kushen injection synergistically improves the efficacy of chemotherapy by modulating the tumor environment of breast cancer

“…These compounds included eight alkaloids and derivatives (4 1 , 5, 8, 9, 10, 11 1 , 11 2 , 11 3 , 13), five organic acids and derivatives (3, 14, 19, 20, 21), five organic oxygen compounds (2, 4 2 , 6, 16, 17, 18), three benzenoids (7, 12, 25), two phenylpropanoids and polyketides (24, 28), one organic nitrogen compound (1), one lipids and lipid-like molecule (22), and one organoheterocyclic compound (26). Consistent with previous findings ( 35 , 38 , 56 ), we have also determined six alkaloids matrine, oxymatrine, N-methylcytisine, sophoridine, sophocarpine and oxysophocarpine, which have been known as the primary active ingredients of CKI.…”

“…In addition, the energy metabolism and DNA repair pathways of MDA-MB-231 cells are reduced after CKI intervention ( 62 ). Our previous research also reveals potential immunotherapy biomarkers of CKI on TNBC by applying transcriptome data mining ( 38 ). Collectively, existing clinical and experimental results indicate that CKI holds a great promise as an adjuvant for anticancer immunotherapy.…”

“…These clinical and experimental evidence suggested that CKI has great potential to serve as an adjuvant for anticancer immunotherapy. Our previous research also revealed possible immunotherapy biomarkers of CKI on TNBC by transcriptome data mining ( 38 ). Therefore, considering the immunoregulatory effects of CKI on the TME of HCC and its broad-spectrum anticancer activity, we aimed to study whether the combination of CKI and chemotherapy could increase the anti-tumor immunity in TNBC.…”

Machine learning algorithms assisted identification of post-stroke depression associated biological features

“…Mutations of FERMT3 gene could cause leukocyte adhesion deficiency type III (LAD III) ( Kuijpers et al, 2009 ). Liu et al (2021) performed RNA sequencing in patients with triple-negative breast cancer and identified FERMT3 as protective gene in compound kushen injection treatment. Nonetheless, correlations of FERMT3 and SDHD with stroke have not been previously reported.…”

“…Module membership (MM) and gene significance (GS) were estimated to connect modules with clinical characteristics. Hub gene modules were designated as those with the highest Pearson module membership correlation and P -value < 0.05 ( Liu et al, 2021 ).…”