METHODS: Smaller micro tissues (˂150 μm in diameter) mixed with Matrigel were engrafted subcutaneously into NSG mice to generate the passage 1 (P1) patient-derived xenograft. The micro tumours from P1 patient-derived xenograft were then excised and orthotopically xenografted into another batch of NSG mice to generate a metastatic colorectal cancer patient-derived xenograft, P2. Haematoxylin and eosin and immunohistochemistry staining were performed to compare the characters between patient-derived xenograft tumours and primary tumours.

RESULTS: About 16 out of 18 P1 xenograft models successfully grew a tumour for 50.8 ± 5.1 days (success rate 89.9%). Six out of eight P1 xenograft models originating from metastatic patients successfully grew tumours in the colon and metastasized to liver or lung in the NSG recipients for 60.9 ± 4.5 days (success rate 75%). Histological examination of both P1 and P2 xenografts closely resembled the histological architecture of the original patients' tumours. Immunohistochemical analysis revealed similar biomarker expression levels, including CDH17, Ki-67, active β-catenin, Ki-67 and α smooth muscle actin when compared with the original patients' tumours. The stromal components that support the growth of patient-derived xenograft tumours were of murine origin.

METHOD: Relevant studies detecting SMAD4 expression in cancer patients treated with chemo-drugs up till December 2020 were systematically searched in four common scientific databases using selected keywords. The pooled hazard ratio (HR) was the ratio of hazard rate between SMAD4neg population vs SMAD4pos population. The HRs and risk ratios (RRs) with 95% confidence intervals (CIs) were used to explore the association between SMAD4 expression losses with drug resistance in cancers.

RESULT: After an initial screening according to the inclusion and exclusion criteria, eleven studies were included in the meta-analysis. There were a total of 2092 patients from all the included studies in this analysis. Results obtained indicated that loss of SMAD4 expression was significantly correlated with drug resistance with pooled HRs (95% CI) of 1.23 (1.01-1.45), metastasis with pooled RRs (95% CI) of 1.10 (0.97-1.25) and recurrence with pooled RRs (95% CI) of 1.32 (1.06-1.64). In the subgroup analysis, cancer type, drug type, sample size and antibody brand did not affect the significance of association between loss of SMAD4 expression and drug resistance. In addition, there was no evidence of publication bias as suggested by Begg's test.

METHODS: A total of 236 breast cancer patients from China completed the Chinese Version of the Posttraumatic Stress Disorder Symptom Scale (PSS), the Chinese version of the Patient Health Questionnaire (PHQ-9), the Chinese version of the General Anxiety Symptoms Scale (GAD-7). In addition, caregivers of these breast cancer patients were surveyed by the Caregiver Self-Assessment Questionnaire (CSAQ).

RESULTS: Structural equation model showed that our model fitted well [χ2 /df = 1.966, TLI = 0.959, CFI = 0.994, RMSEA (90% CI) = 0.065 (0-0.12)] and revealed that anxiety, but not depression, mediated the relationship between PTSS in breast cancer patients and caregiver burden.

METHODS: G. lucidum samples from various sources and in varying stages were identified by using δ 13C, δD, δ 18O, δ 15N, C, and N contents combined with chemometric tools. Chemometric approaches, including PCA, OPLS-DA, PLS, and FLDA models, were applied to the obtained data. The established models were used to trace the origin of G. lucidum from various sources or track various stages of G. lucidum.

RESULTS: In the stage model, the δ 13C, δD, δ 18O, δ 15N, C, and N contents were considered meaningful variables to identify various stages of G. lucidum (bud development, growth, and maturing) using PCA and OPLS-DA and the findings were validated by the PLS model rather than by only four variables (δ 13C, δD, δ 18O, and δ 15N). In the origin model, only four variables, namely δ 13C, δD, δ 18O, and δ 15N, were used. PCA divided G. lucidum samples into four clusters: A (Zhejiang), B (Anhui), C (Jilin), and D (Fujian). The OPLS-DA model could be used to classify the origin of G. lucidum. The model was validated by other test samples (Pseudostellaria heterophylla), and the external test (G. lucidum) by PLS and FLDA models demonstrated external verification accuracy of up to 100%.

METHOD: Relevant studies detecting the expression or SNP of CYP24A1 in cancer patients up till May 2022 were systematically searched in four common scientific databases including PubMed, EMBASE, Cochrane library and ISI Web of Science. The pooled hazard ratios (HRs) indicating the ratio of hazard rate of survival time between CYP24A1high population vs CYP24A1low population were calculated. The pooled HRs and odds ratios (ORs) with 95% confidence intervals (CIs) were used to explore the association between CYP24A1's expression or SNP with survival, metastasis, recurrence, and drug resistance in cancer patients.

RESULT: Fifteen studies were included in the meta-analysis after an initial screening according to the inclusion and exclusion criteria. There was a total of 3784 patients pooled from all the included studies. Results indicated that higher expression or SNP of CYP24A1 was significantly correlated with shorter survival time with pooled HRs (95% CI) of 1.21 (1.12, 1.31), metastasis with pooled ORs (95% CI) of 1.81 (1.11, 2.96), recurrence with pooled ORs (95% CI) of 2.14 (1.45, 3.18) and drug resistance with pooled HRs (95% CI) of 1.42 (1.17, 1.68). In the subgroup analysis, cancer type, treatment, ethnicity, and detection approach for CYP24A1 did not affect the significance of the association between CYP24A1 expression and poor prognosis.