Effect of Chinese herbs on stage I-III CRC
A total of 707 patients were finally included (Fig. 1), of which 246 were in the control group and 461 were in the TCM group (Table 1). A total of 408 of 461 patients treated with TCM had adenocarcinoma compared with 197 of 246 control patients (P = 0.012); the difference in histology between the two groups was significant (P = 0.019). A total of 381 patients received adjuvant chemotherapy in the TCM group, and 185 patients received adjuvant chemotherapy in the control group (P = 0.001). After PSM, the baseline and tumour characteristics were not significantly different between the two groups (Supple Table 1).
Table 1
Baseline and tumor characteristics of patients before propensity score matching.
| TCM group(n = 461) | Control group(n = 246) | P value |
age (y) | | | |
༜60 | 179 | 80 | 0.097 |
≥ 60 | 282 | 166 |
gender | | | |
male | 248 | 136 | 0.705 |
female | 213 | 110 |
location | | | |
colon | 288 | 145 | 0.359 |
rectum | 173 | 101 |
pathology | | | |
adenocarcinoma | 408 | 197 | 0.012* |
non-adenocarcinoma | 2 | 2 |
unknown | 51 | 47 |
histodifferentiation | | | |
poorly | 50 | 29 | 0.019* |
moderately | 291 | 127 |
well | 11 | 2 |
known | 109 | 88 |
TNM stage | | | |
II | 225 | 137 | 0.081 |
III | 236 | 109 |
chemotherapy | | | |
yes | 381 | 185 | 0.023* |
no | 80 | 61 |
radiotherapy | | | |
yes | 37 | 19 | 0.887 |
no | 424 | 227 |
comorbidities | | | |
yes | 235 | 103 | 0.021* |
no | 226 | 143 |
* statistical difference |
The cumulative DFS after 1 to 6 years in the control group was 61%, 52%, 46%, 45%, 42% and 35%. The cumulative DFS in the TCM group was 76%, 66%, 59%, 56%, 56% and 52%. Before matching, the median DFS (mDFS) of the TCM group was not attached (Fig. 2A, HR: 0.61, log-rank P༜0.05). After matching, the risk of metastatic recurrence decreased in the TCM group (Fig. 2B, HR: 0.59, log-rank P༜0.05), although the mDFS was also not attached in the TCM group.
Identification of the core combination
Complete TCM prescriptions were retrieved for 314 of 461 patients and included 384 herbs. The results of the relevance analysis are shown in Supplemental Table 2. Among these, Fuling → Yinchen, Baizhu (A, Support: 29.53%, Confidence: 87.14%), Baizhu → Fuling, Huangqin (B, Support: 27.00%, Confidence: 96.88%), Baizhu → Yinchen, Chenpi, and Fuling (C, Support: 19.41%, Confidence: 100%) were the combinations with the highest support.
The risk of metastatic recurrence in patients treated with the C combination was significantly lower than that in the control group (Fig. 3A, HR: 0.43, log-rank P = 0.003). In addition, patients treated with the C combination were further compared with the TCM group, and there was no survival difference between these two groups (Fig. 3B, HR: 1.46, log-rank P = 0.184).
Ingredients and targets of the core combination
There was a total of 45 ingredients in the herbs of the C combination based on OB and DL. Among these, 7 originated from Baizhu, 15 originated from Fuling, 10 originated from Chenpi, and 13 originated from Yinchen. Then, 216 targets associated with the above ingredients were matched. After being assessed in detail, 8 targets were excluded due to duplication. Finally, 208 ingredient-related targets were confirmed, and the PPI network is shown in Supplemental Fig. 1.
CRC-related targets of the core combination
CRC-related targets were retrieved from four databases: 81 from OMIM, 359 from GAD, 49 from TTD and 1058 from PharmGkb. After duplicate removal, 1076 targets were finally confirmed.
Then, a merged PPI network of ingredients/CRC-related targets was generated, and the network indicated that there were 96 CRC-related targets in the core combination. These targets correspond to MOL000049 of Baizhu, MOL000098, MOL000354 and MOL000358 of Yinchen, MOL000273 and MOL000296 of Fuling, and MOL004328, MOL005100, MOL005815 and MOL005828 of Chenpi (Fig. 4).
Enrichment analysis
Of the 96 targets, 30 were excluded due to a lack of corresponding reported pathways, and 36 were excluded due to their DC being under the average value of 14.6, so 30 targets were finally subjected to GO and KEGG analysis.
There were 327 biological processes included, and they were mainly clustered in the following categories: 1) positive regulation of transcription from the RNA polymerase II promoter (55.2%), 2) positive regulation of transcription, DNA-templated (51.7%), 3) positive regulation of cell proliferation (41.4%), 4) positive regulation of protein phosphorylation (37.9%), 5) MAPK cascade (37.9%), 6) negative regulation of apoptotic process (37.9%), 7) signal transduction (37.9%), 8) positive regulation of gene expression (31.0%), 9) inflammatory response (31.0%); and 10) positive regulation of the ERK1 and ERK2 cascade (27.6%) (Fig. 5A).
In addition, pathways involved in cancer was the highest term (75.9%) among the 111 KEGG pathways, and the enrichment proportions of the PI3K-Akt pathway (48.3%), MAPK signalling pathway (44.8%), and HIF-1 signalling pathway (37.9%) were in decreasing order (Fig. 5B).