Photodynamic therapy improves the outcome of immune checkpoint inhibitors via remodelling anti-tumour immunity in patients with gastric cancer

BACKGROUND

Photodynamic therapy (PDT) plays an immunoregulatory role in tumours. Here, we conducted a retrospective patient analysis to evaluate the effectiveness of PDT plus immune checkpoint inhibitors (ICIs) in gastric cancer. Further, we performed a dynamic analysis of gastric cancer patients receiving PDT to clarify its effects on anti-tumour immunity.

METHODS

Forty ICI-treated patients that received PDT or not were retrospectively analysed. Five patients with gastric adenocarcinoma were enrolled for sample collection before and after PDT. Single-cell RNA/T cell receptor (TCR) sequencing, flow cytometry and histological exanimation were used to analyse the collected specimens.

RESULTS

Patients in PDT group had a significantly better OS after ICI treatment than those in No PDT group. Single-cell analysis identified ten cell types in gastric cancer tissues and four sub-populations of T cells. Immune cell infiltration increased in the tumours after PDT and the circular immune cells showed consistent alterations. TCR analysis revealed a specific clonal expansion after PDT in cytotoxic T lymphocytes (CTL), but a constriction in Tregs. The B2M gene is upregulated in tumour cells after PDT and is associated with immune cell infiltration. Several pathways involving the positive regulation of immunity were enriched in tumour cells in the post-PDT group. The interactions following PDT were increased between tumour cells and effector cells but decreased between Tregs and other immune cells. Some co-stimulatory signaling emerged, whereas co-inhibitory signaling disappeared in intercellular communication after PDT.

CONCLUSIONS

PDT elicits an anti-tumour response through various mechanisms and is promising as an adjuvant to enhance ICI benefit.

A novel adenosine signalling-based prognostic signature in gastric cancer and its association with cancer immune features and immunotherapy response

Reliable prognostic signatures that can reflect the intrinsic characteristics of gastric cancer (GC) are still rare. Here, we developed an adenosine-based prognostic signature and explored its association with the tumour immune in GC patients, aiming at confirming the prognostic value of adenosine-related genes and guiding the GC risk stratification and immunotherapeutic response prediction. We collected adenosine pathway-related genes from STRING websites and manual searching. We enrolled the The Cancer Genome Atlas cohort and four gene expression omnibus cohorts of GC for generating and validating the adenosine pathway-based signature using the Cox regression method. Gene expression in the signature was verified using polymerase chain reaction. We also performed gene set enrichment analysis, immune infiltration assessment and immunotherapy response prediction based on this signature. Our study resulted in a six-gene adenosine signature (GNAS, CXCR4, PPP1R1B, ADCY6, NT5E and NOS3) for risk stratification of GC prognosis, with the highest area under the receiver operating characteristic curve up to 0.767 for predicting 10-year overall survival (OS). In the training cohort, patients with signature-defined high risk had significantly poorer OS than those with low risk (p < .001). Multivariate analysis identified the signature as an independent prognostic factor (hazard ratio 2.863, 95% confidence interval [1.871-4.381], p < .001). These findings were confirmed in four independent cohorts. Expression detection showed that all signature genes were upregulated in both GC tissues and cell lines. Further analysis revealed that the signature-defined high-risk patients were characterised by immunosuppressive states and associated with a poor immunotherapy response. In conclusion, the adenosine pathway-based signature represents a promising risk stratification tool for GC in guiding individualised prognostication and immunotherapy.

Lipid Nanoparticles-Based Therapy in Liver Metastasis Management: From Tumor Cell-Directed Strategy to Liver Microenvironment-Directed Strategy

Metastasis to the liver, as one of the most frequent metastatic patterns, was associated with poor prognosis. Major drawbacks of conventional therapies in liver metastasis were the lack of metastatic-targeting ability, predominant systemic toxicities and incapability of tumor microenvironment modulations. Lipid nanoparticles-based strategies like galactosylated, lyso-thermosensitive or active-targeting chemotherapeutics liposomes have been explored in liver metastasis management. This review aimed to summarize the state-of-art lipid nanoparticles-based therapies in liver metastasis management. Clinical and translational studies on the lipid nanoparticles in treating liver metastasis were searched up to April, 2023 from online databases. This review focused not only on the updates in drug-encapsulated lipid nanoparticles directly targeting metastatic cancer cells in treating liver metastasis, but more importantly on research frontiers in drug-loading lipid nanoparticles targeting nonparenchymal liver tumor microenvironment components in treating liver metastasis, which showed promise for future clinical oncological practice.

Bioinformatics combined with quantitative proteomics analyses and identification of potential biomarkers in cholangiocarcinoma

BACKGROUND

Cholangiocarcinoma (CCA) is an invasive malignancy arising from biliary epithelial cells; it is the most common primary tumour of the bile tract and has a poor prognosis. The aim of this study was to screen prognostic biomarkers for CCA by integrated multiomics analysis.

METHODS

The GSE32225 dataset was derived from the Gene Expression Omnibus (GEO) database and comprehensively analysed by using R software and The Cancer Genome Atlas (TCGA) database to obtain the differentially expressed RNAs (DERNAs) associated with CCA prognosis. Quantitative isobaric tags for relative and absolute quantification (iTRAQ) proteomics was used to screen differentially expressed proteins (DEPs) between CCA and nontumour tissues. Through integrated analysis of DERNA and DEP data, we obtained candidate proteins APOF, ITGAV and CASK, and immunohistochemistry was used to detect the expression of these proteins in CCA. The relationship between CASK expression and CCA prognosis was further analysed.

RESULTS

Through bioinformatics analysis, 875 DERNAs were identified, of which 10 were associated with the prognosis of the CCA patients. A total of 487 DEPs were obtained by using the iTRAQ technique. Comprehensive analysis of multiomics data showed that CASK, ITGAV and APOF expression at both the mRNA and protein levels were different in CCA compared with nontumour tissues. CASK was found to be expressed in the cytoplasm and nucleus of CCA cells in 38 (45%) of 84 patients with CCA. Our results suggested that patients with positive CASK expression had significantly better overall survival (OS) and recurrence-free survival (RFS) than those with negative CASK expression. Univariate and multivariate analyses demonstrated that negative expression of CASK was a significantly independent risk factor for OS and RFS in CCA patients.

CONCLUSIONS

CASK may be a tumour suppressor; its low expression is an independent risk factor for a poor prognosis in CCA patients, and so it could be used as a clinically valuable prognostic marker.