Objectives: Elevated circulating DNA (cirDNA) concentrations were found to be associated with trauma or tissue damage which suggests involvement of inflammation or cell death in post-operative cirDNA release. We carried out the first prospective, multicenter study of the dynamics of cirDNA and neutrophil extracellular trap (NETs) markers during the perioperative period from 24 h before surgery up to 72 h after curative surgery in cancer patients.

Methods: We examined the plasma levels of two NETs protein markers [myeloperoxidase (MPO) and neutrophil elastase (NE)], as well as levels of cirDNA of nuclear (cir-nDNA) and mitochondrial (cir-mtDNA) origin in 29 colon, prostate, and breast cancer patients and in 114 healthy individuals (HI).

Results: The synergistic analytical information provided by these markers revealed that: (i) NETs formation contributes to post-surgery conditions; (ii) post-surgery cir-nDNA levels were highly associated with NE and MPO in colon cancer [r = 0.60 (P < 0.001) and r = 0.53 (P < 0.01), respectively], but not in prostate and breast cancer; (iii) each tumor type shows a specific pattern of cir-nDNA and NETs marker dynamics, but overall the pre-and post-surgery median values of cir-nDNA, NE, and MPO were significantly higher in cancer patients than in HI.

Conclusion: Taken as a whole, our work reveals the association of NETs formation with the elevated cir-nDNA release during a cancer patient's perioperative period, depending on surgical procedure or cancer type. By contrast, cir-mtDNA is poorly associated with NETs formation in the studied perioperative period, which would appear to indicate a different mechanism of release or suggest mitochondrial dysfunction.

Background: TP53 mutations and homologous recombination deficiency (HRD) occur frequently in breast cancer. However, the characteristics of TP53 pathogenic mutations in breast cancer patients with/without HRD are not clear.

Methods: Clinical next-generation sequencing (NGS) of both tumor and paired blood DNA from 119 breast cancer patients (BRCA-119 cohort) was performed with a 520-gene panel. Mutations, tumor mutation burden (TMB), and genomic HRD scores were assessed from NGS data. NGS data from 47 breast cancer patients in the HRD test cohort were analyzed for further verification.

Results: All TP53 pathogenic mutations in patients had somatic origin, which was associated with the protein expression of estrogen receptor and progestogen receptor. Compared to patients without TP53 pathologic mutations, patients with TP53 pathologic mutations had higher levels of HRD scores and different genomic alterations. The frequency of TP53 pathologic mutation was higher in the HRD-high group (HRD score ≥ 42) relative to that in the HRD-low group (HRD score < 42). TP53 has different mutational characteristics between the HRD-low and HRD-high groups. TP53-specific mutation subgroups had diverse genomic features and TMB. Notably, TP53 pathogenic mutations predicted the HRD status of breast cancer patients with an area under the curve (AUC) of 0.61. TP53-specific mutations, namely HRD-low mutation, HRD-high mutation, and HRD common mutation, predicted the HRD status of breast cancer patients with AUC values of 0.32, 0.72, and 0.58, respectively. Interestingly, TP53 HRD-high mutation and HRD common mutation combinations showed the highest AUC values (0.80) in predicting HRD status.

Conclusions: TP53-specific mutation combinations predict the HRD status of patients, indicating that TP53 pathogenic mutations could serve as a potential biomarker for poly-ADP-ribose polymerase (PARP) inhibitors in breast cancer patients.

Background: Lung squamous cell carcinoma (LUSC) lacks effective targeted therapies and has a poor prognosis. Disruption of squalene epoxidase (SQLE) has been implicated in metabolic disorders and cancer. However, the role of SQLE as a monooxygenase involved in oxidative stress remains unclear.

Methods: We analyzed the expression and prognosis of lung adenocarcinoma (LUAD) and LUSC samples from GEO and TCGA databases. The proliferative activity of the tumors after intervention of SQLE was verified by cell and animal experiments. JC-1 assay, flow cytometry, and Western blot were used to show changes in apoptosis after intervention of SQLE. Flow cytometry and fluorescence assay of ROS levels were used to indicate oxidative stress status.

Results: We investigated the unique role of SQLE expression in the diagnosis and prognosis prediction of LUSC. Knockdown of SQLE or treatment with the SQLE inhibitor terbinafine can suppress the proliferation of LUSC cells by inducing apoptosis and reactive oxygen species accumulation. However, depletion of SQLE also results in the impairment of lipid peroxidation and ferroptosis resistance such as upregulation of glutathione peroxidase 4. Therefore, prevention of SQLE in synergy with glutathione peroxidase 4 inhibitor RSL3 effectively mitigates the proliferation and growth of LUSC.

Conclusion: Our study indicates that the low expression of SQLE employs adaptive survival through regulating the balance of apoptosis and ferroptosis resistance. In future, the combinational therapy of targeting SQLE and ferroptosis could be a promising approach in treating LUSC.

Background: The prognosis of breast cancer is often unfavorable, emphasizing the need for early metastasis risk detection and accurate treatment predictions. This study aimed to develop a novel multi-modal deep learning model using preoperative data to predict disease-free survival (DFS).

Methods: We retrospectively collected pathology imaging, molecular and clinical data from The Cancer Genome Atlas and one independent institution in China. We developed a novel Deep Learning Clinical Medicine Based Pathological Gene Multi-modal (DeepClinMed-PGM) model for DFS prediction, integrating clinicopathological data with molecular insights. The patients included the training cohort (n = 741), internal validation cohort (n = 184), and external testing cohort (n = 95).

Result: Integrating multi-modal data into the DeepClinMed-PGM model significantly improved area under the receiver operating characteristic curve (AUC) values. In the training cohort, AUC values for 1-, 3-, and 5-year DFS predictions increased to 0.979, 0.957, and 0.871, while in the external testing cohort, the values reached 0.851, 0.878, and 0.938 for 1-, 2-, and 3-year DFS predictions, respectively. The DeepClinMed-PGM's robust discriminative capabilities were consistently evident across various cohorts, including the training cohort [hazard ratio (HR) 0.027, 95% confidence interval (CI) 0.0016-0.046, P < 0.0001], the internal validation cohort (HR 0.117, 95% CI 0.041-0.334, P < 0.0001), and the external cohort (HR 0.061, 95% CI 0.017-0.218, P < 0.0001). Additionally, the DeepClinMed-PGM model demonstrated C-index values of 0.925, 0.823, and 0.864 within the three cohorts, respectively.

Conclusion: This study introduces an approach to breast cancer prognosis, integrating imaging and molecular and clinical data for enhanced predictive accuracy, offering promise for personalized treatment strategies.

Background: Myeloid differentiation factor 88 (MyD88) is the core adaptor for Toll-like receptors defending against microbial invasion and initiating a downstream immune response during microbiota-host interaction. However, the role of MyD88 in the pathogenesis of inflammatory bowel disease is controversial. This study aims to investigate the impact of MyD88 on intestinal inflammation and the underlying mechanism.

Methods: MyD88 knockout (MyD88^−/−) mice and the MyD88 inhibitor (TJ-M2010-5) were used to investigate the impact of MyD88 on acute dextran sodium sulfate (DSS)-induced colitis. Disease activity index, colon length, histological score, and inflammatory cytokines were examined to evaluate the severity of colitis. RNA transcriptome analysis and 16S rDNA sequencing were used to detect the potential mechanism.

Results: In an acute DSS-colitis model, the severity of colitis was not alleviated in MyD88^−/− mice and TJ-M2010-5-treated mice, despite significantly lower levels of NF-κB activation being exhibited compared to control mice. Meanwhile, 16S rDNA sequencing and RNA transcriptome analysis revealed a higher abundance of intestinal Proteobacteria and an up-regulation of the nucleotide oligomerization domain-like receptors (NLRs) signaling pathway in colitis mice following MyD88 suppression. Further blockade of the NLRs signaling pathway or elimination of gut microbiota with broad-spectrum antibiotics in DSS-induced colitis mice treated with TJ-M2010-5 ameliorated the disease severity, which was not improved solely by MyD88 inhibition. After treatment with broad-spectrum antibiotics, downregulation of the NLR signaling pathway was observed.

Conclusion: Our study suggests that the suppression of MyD88 might be associated with unfavorable changes in the composition of gut microbiota, leading to NLR-mediated immune activation and intestinal inflammation.