From July 2024 to August 2025, a total of 96 patients diagnosed with advanced colorectal cancer were enrolled. Based on the inclusion and exclusion criteria, 56 patients were excluded, which included 18 cases in the terminal stage of wasting syndrome, 12 cases with severe organ dysfunction, 23 cases who had used antibiotics within the past 3 months, 1 case unable to take oral medication, and 2 cases with other tumors. Ultimately, 40 patients were included in the study. All patients completed 6 months of standardized chemotherapy and efficacy assessment, and provided fecal and blood samples both before and 6 months after chemotherapy for the detection of intestinal flora and blood indicators. There was no loss or exclusion of samples.

Inclusion criteria: 1) Confirmed diagnosis of colorectal cancer through pathological examination, with clinical stage of II - IV (mid-late stage) [11]; 2) Meets the diagnostic criteria for cancer cachexia and is diagnosed as the cachexia stage [12]; 3) According to the NCCN guidelines, chemotherapy is required, and the patient can tolerate the treatment [13]; 4) More than 21 days have elapsed since the last surgery, radiotherapy, chemotherapy, targeted therapy, immunotherapy, etc.; 5) There is a risk of malnutrition (NRS2002) with a score of ≥3, and enteral nutrition support treatment is required [14]; 6) The patient’s physical condition score on the KPS scale is ≥70 points, and they are capable of taking care of themselves in daily life [15]; 7) Age and Gender: Over 18 years old, gender not restricted; 8) Expected survival period: ≥6 months; 9) No use of antibiotics in the past 3 months; 10) At least one measurable lesion meeting the RECIST 1.1 criteria was required.

Exclusion criteria: 1) According to the diagnostic criteria for cancer cachexia, those diagnosed as the refractory stage of cachexia (expected lifespan < 3 months); 2) Comorbidities: patients with severe dysfunction of the heart, lung, liver, or kidney; 3) Concurrently having other tumors or having participated in other clinical trials. This study was approved by the Ethical Committee of Youjiang Medical University for Nationalities. The ethical review number: 2024070202. All patients were informed and signed the informed consent form.

This study included patients with stage II - IV colorectal cancer, all of whom satisfied the criteria for advanced stages and required standard first-line chemotherapy. The treatment principles and efficacy evaluation criteria remained consistent. The predominant pathological type was adenocarcinoma, with a minimal proportion of squamous cell carcinoma. The overall pathological composition was uniform.

Patients with advanced colorectal cancer cachexia who met the inclusion and exclusion criteria were given chemotherapy according to the 2023 NCCN colorectal cancer guidelines (oxaliplatin + leucovorin + 5-fluorouracil, mFOLFOX6 regimen; or oxaliplatin + capecitabine, XELOX regimen; or irinotecan + leucovorin + 5-fluorouracil, FOLFIRI regimen) [16]. From the start of the first chemotherapy cycle to the end of the last chemotherapy cycle, a total of 6 months (including 6 - 8 chemotherapy cycles) were covered. After completing the standardized chemotherapy, a review of abdominal CT was conducted at the 6th month of follow-up. Based on the imaging results, the patients were classified into 3 groups according to the Response Evaluation Criteria in Solid Tumors (RECIST 1.1 version) [17]. The chemotherapy regimens for the three patient groups are as follows: The remission group included 14 cases of the mFOLFOX6 regimen, 5 cases of the XELOX regimen, and 3 cases of the FOLFIRI regimen; the stable group comprised 4 cases of the mFOLFOX6 regimen, 1 case of the XELOX regimen, and 3 cases of the FOLFIRI regimen; the progression group consisted of 5 cases of the mFOLFOX6 regimen, 3 cases of the XELOX regimen, and 2 cases of the FOLFIRI regimen. For patients in stages II - IV included in this study, baseline confirmation was achieved through full abdominal CT, which identified measurable lesions (target lesions) that satisfied the RECIST 1.1 criteria. For non-metastatic patients in stages II and III, the primary lesion was designated as the target lesion, whereas for stage IV patients, the target lesion comprised the primary lesion ± metastatic lesion. The measurement methods and evaluation criteria have been thoroughly standardized.

Before chemotherapy and at the end of the last chemotherapy (after 6 months of treatment), the following contents should be recorded: nutritional risk screening score sheet (NRS2002), Karnofsky performance status (KPS) score, body mass index (BMI), grip strength (in kg), body composition analysis, and abdominal CT imaging examination. Venous blood was drawn in the morning to test relevant indicators: hemoglobin (Hb), total protein (TP), albumin (ALB), prealbumin (PA), and C-reactive protein (CRP). Fecal samples were collected to test the intestinal microbiota.

During sample collection, instruct the patient to urinate first. Place clean and hygienic toilet paper in the toilet to prevent urine contamination. Use a disposable sterile stool sampling box to collect 200 - 500 mg of fresh fecal mid-section internal samples. The sampling should be completed within 2 hours of the marked time. After marking, store the samples at −80˚C in the refrigerator within 6 hours. During the sample preparation stage, weigh 200mg of the mixed fecal sample, add PBS solution, shake it, then centrifuge at 10,000 rpm for 3 minutes and discard the supernatant. Use the E.Z.N.A^TM Mag-Bind soil DNA kit to extract the fecal genomic DNA. Target the V3-V4 variable region of the 16S rRNA gene, and perform PCR amplification using the forward primer：5'-CTACGGGCGCAG-3' and the reverse primer：5'-GACTACHVGGTATCATCC-3'. Quantify the library concentration using the Qubit 3.0 fluorescence quantitative instrument and sequence the two-round amplification products. Data analysis is conducted using the RDP, Silva, and NCBI 16S databases for comparison, and analyses of intestinal microbiota diversity and composition are carried out. The fecal 16S rRNA sequencing detection is performed [18]. This experiment was supported by Shenggong Biotechnology Engineering (Shanghai) Co., Ltd.

1) Sample quality: The fecal samples were refrigerated within 2 hours after collection to prevent bacterial contamination; the blood biochemistry, grip strength, and body composition tests were all conducted by the same laboratory and the same operator to ensure uniform testing methods.

2) Efficacy assessment: The CT examinations were evaluated by two experienced radiologists in a double-blind manner. In case of disagreement, consensus was reached through consultation to reduce assessment errors.

3) Statistical methods: Statistical analysis was performed using Prism software, and the data analysis results were verified by the supervisor.

Statistical analysis was performed using GraphPad Prism (version 9.5) software [19]. For the measurement data, the Shapiro-Wilk test is used to determine whether the data conform to a normal distribution [20]. The measurement data that follow a normal distribution are expressed as mean ± standard deviation (SD). The measurement data that do not follow a normal distribution are expressed by the median (M) and interquartile range (IQR). The comparisons among multiple groups were conducted using one-way analysis of variance or Kruskal-Wallis test, and pairwise comparisons between groups were performed using the Least Significant Difference (LSD) test or Dunnett T3 test [21]. The comparison within this group before and after treatment is performed using the paired sample t-test or the Wilcoxon signed-rank test [22]. For the count data, they are expressed as frequencies and percentages (n, %), and the chi-square test is used. For intestinal microbiota analysis, the Benjamini-Hochberg (BH) method was employed to correct for multiple comparisons. The Adonis (PERMANOVA) test was used to assess the beta diversity. The LEfSe analysis incorporated built-in corrections and LDA threshold controls to mitigate false positives. The application of the receiver operating characteristic curve (ROC) was used to assess the predictive performance of various baseline alpha diversity indices for chemotherapy remission by computing the area under the curve (AUC) and corresponding P-value. When the P-value is less than 0.05, the difference is statistically significant.

From July 2024 to August 2025, a total of 40 patients with advanced colorectal cancer cachexia who met the criteria were included. After 6 months of treatment, there were 22 cases in the response group (complete response + partial response, RG), 8 cases in the stable group (SDG), and 10 cases in the progression group (PDG). The general clinical data, including gender, age, BMI, lesion location (colon, rectum), pathological type (adenocarcinoma, squamous cell carcinoma), and TNM stage (II, III, IV), showed no statistically significant differences among the groups (P > 0.05) (Table 1).

Table 1. Comparison of general clinical data of patients in each group [n (%), (mean ± SD).

Note: BMI: Body Mass Index.

Before treatment, there was no statistically significant difference in the nutritional risk screening (NRS 2002) score, BMI (body mass index), HG (grip strength), KPS score, and CRP (C-reactive protein) among the groups (P > 0.05) (Figure 1). After treatment, there was no statistically significant difference in the nutritional risk screening (NRS 2002) score, BMI, HG, KPS score, and CRP among the groups (P > 0.05) (Figure 2). However, there was no statistically significant difference in the paired comparison of the above nutrition-related indicators before and after treatment within the same group (P > 0.05) (Figure 1 and Figure 2).

Figure 1. Nutrition-related indicators of patients in each group before treatment. (A) Nutritional risk screening score; (B) Grip strength; (C) Body mass index; (D) C-reactive protein; (E) KPS score. RG: Remission group; SDG: Stable group; PDG: Progressive group.

Figure 2. Nutrition-related indicators of patients in each group after treatment. (A) Nutritional risk screening score; (B) Grip strength; (C) Body mass index; (D) C-reactive protein; (E) KPS score; RG: Remission group; SDG: Stable group; PDG: Progressive group.

Before treatment, there was no statistically significant difference in serum total protein (TP), albumin (ALB), prealbumin (PA), and hemoglobin (HB) among all groups (P > 0.05) (Figure 3). After treatment, there was no statistically significant difference in serum total protein (TP), albumin (ALB), prealbumin (PA), and hemoglobin (HB) among all groups (P > 0.05) (Figure 4). However, there was no statistically significant difference in the paired comparison of the above blood indicators before and after treatment within the same group (P > 0.05) (Figure 3 and Figure 4).

Figure 3. Nutrition-related blood indicators of patients in each group before treatment. (A) Total protein; (B) Albumin; (C) Prealbumin; (D) Hemoglobin; RG: Remission group; SDG: Stable group; PDG: Progressive group.

Before treatment, there was no statistically significant difference in fat mass index (FMI), fat-free mass index (FFMI), skeletal muscle mass index (SMI), and extracellular water ratio (ECW/TBW) among the groups (P > 0.05) (Figure 5). After treatment, there was no statistically significant difference in fat mass index (FMI), fat-free mass index (FFMI), skeletal muscle mass index (SMI), and extracellular water ratio (ECW/TBW) among the groups (P > 0.05) (Figure 6). However, there was no statistically significant difference in the paired comparison of the above body composition indicators before and after treatment within the same group (P > 0.05) (Figure 5 and Figure 6).

Figure 4. Nutrition-related blood indicators of patients in each group after treatment. (A) Total protein; (B) Albumin; (C) Prealbumin; (D) Hemoglobin; RG: Remission group; SDG: Stable group; PDG: Progressive group.

Figure 5. Body composition of patients in each group before treatment. (A) Fat mass index; (B) Lean body mass index; (C) Skeletal muscle mass index; (D) Extracellular water ratio; RG: Remission group; SDG: Stable group; PDG: Progressive group.

Figure 6. Body composition of patients in each group after treatment. (A) Fat mass index; (B) Lean body mass index; (C) Skeletal muscle mass index; (D) Extracellular water ratio; RG: Remission group; SDG: Stable group; PDG: Progressive group.

Before treatment, the ACE index and Chao1 index of the intestinal microbiota in the RG group were significantly higher than those in the SDG group and the PDG group (P < 0.05), while the Shannon index and Simpson index were significantly higher in the RG group than in the PDG group (P < 0.01) (Figure 7). After treatment, the ACE index, Chao1 index, and Shannon index of the intestinal microbiota in the RG group were significantly higher than those in the SDG group and the PDG group (P < 0.01), and the Simpson index was significantly higher in the RG group than in the PDG group (P < 0.001) (Figure 8).

Principal coordinate analysis (PCoA) based on Bray-Curtis distance shows [23]. Before treatment, the samples of each group were highly overlapping, and there was no statistically significant difference in the overall structure of the intestinal microbiota among the groups (P > 0.05) (Figure 9(A)). After treatment, the samples of each group still did not form distinct, separate clusters (P > 0.05) (Figure 9).

The Venn diagram analysis shows that before treatment, the total number of core bacterial species common to all groups was 112, and the number of unique species was 6 in the RG group, 40 in the SDG group, and 60 in the PDG group. After treatment, the total number of core bacterial species common to all groups was 113, and the number of unique species was 5 in the RG group, 59 in the SDG group, and 41 in the PDG group (Figure 10).

Figure 7. Alpha diversity of intestinal microbiota before treatment in each group of patients. (A) ACE index; (B) Chao1 index; (C) Shannon index; (D) Simpson index; RG: Remission group; SDG: Stable group; PDG: Progression group. *P < 0.05; **P < 0.01; ***P < 0.001; ****P < 0.0001.

Figure 8. Alpha diversity of intestinal microbiota in each group of patients after treatment. (A) ACE index; (B) Chao1 index; (C) Shannon index; (D) Simpson index. *P < 0.05; **P < 0.01; ***P < 0.001; ****P < 0.0001; RG: Remission group; SDG: Stable group; PDG: Progression group.

Figure 9. Beta diversity of intestinal microbiota in each group of patients before and after treatment. (A) PCoA analysis of intestinal microbiota in each group of patients before treatment; (B) PCoA analysis of intestinal microbiota in each group of patients after treatment; RG: Remission group; SDG: Stable group; PDG: Progression group.

Figure 10. Analysis of core microbiota species before and after treatment in each group of patients. (A) Core microbiota species of each group of patients before treatment; (B) Core microbiota species of each group of patients after treatment; RG: Remission group; SDG: Stable group; PDG: Progressive group.

At the phylum level, before and after treatment, Firmicutes, Proteobacteria, Actinobacteriota, Verrucomicrobiota, and Bacteroidota accounted for more than 90% of each group (Figure 11). At the genus level, before and after treatment, Escherichia-Shigella, Bifidobacterium, Blautia, Enterococcus, Streptococcus, Lactobacillus, Klebsiella,Akkermansia,Subdoligranulum, and Faecalibacterium accounted for more than 75% of each group (Figure 12).

The LEfSe analysis revealed, before treatment, the top three dominant bacterial groups in the RG group were Faecalibacterium, Burkholderiales, and Erysipelotrichaceae-UCG-003; in the SDG group, the top three were Acidaminococcales, Acidaminococcaceae, and Phascolarctobacterium; and in the progressive group, the top three were Lactoacillaceae,Lactoacillus, and Clostridiales (Figure 13) [24].

Figure 11. Analysis of the composition of intestinal microbiota in patients of each group at the phylum level before and after treatment. (A) Intestinal microbiota of patients in each group at the phylum level before treatment; (B) Intestinal microbiota of patients in each group at the phylum level after treatment; RG: Remission group; SDG: Stable group; PDG: Progressive group.

Figure 12. Analysis of the composition of intestinal microbiota in patients of each group at the genus level before and after treatment. (A) Intestinal microbiota of patients in each group at the genus level before treatment; (B) Intestinal microbiota of patients in each group at the genus level after treatment; RG: Remission group; SDG: Stable group; PDG: Progressive group.

After treatment, the dominant bacterial group in the RG group was Carnobacteriaceae, while in the SDG group it wasDesulfovibrio, Unassigned-Desulfovibrio; in the PDG group, it wasStreptococcaceae, Lactobacillus,Unassigned-Lactobacillus,Streptococcussalivarius, andActinomycetales (Figure 14).

Figure 13.Analysis of species differences in the intestinal microbiota of patients in each group before treatment. RG: Remission group; SDG: Stable group; PDG: Progressive group.

Figure 14.Analysis of species differences in the intestinal microbiota of patients in each group after treatment. RG: Remission group; SDG: Stable group; PDG: Progressive group.

To assess the potential of intestinal microbiota indicators in predicting the baseline efficacy of chemotherapy, ROC prediction analysis revealed that the AUC values for the ACE, Chao1, Shannon, and Simpson indices of the baseline patients’ intestinal microbiota alpha diversity exceeded 0.7, with all results achieving statistical significance (P < 0.05) (Figure 15).

Figure 15. ROC prediction analysis of baseline gut microbiota alpha diversity. RG: Remission group; SDG: Stable group; PDG: Progressive group.