Expression of CD274 mRNA Measured by qRT-PCR Correlates With PD-L1 Immunohistochemistry in Gastric and Urothelial Carcinoma

A comprehensive single-cell breast tumor atlas defines epithelial and immune heterogeneity and interactions predicting anti-PD-1 therapy response

We present an integrated single-cell RNA sequencing atlas of the primary breast tumor microenvironment (TME) containing 236,363 cells from 119 biopsy samples across eight datasets. In this study, we leverage this resource for multiple analyses of immune and cancer epithelial cell heterogeneity. We define natural killer (NK) cell heterogeneity through six subsets in the breast TME. Because NK cell heterogeneity correlates with epithelial cell heterogeneity, we characterize epithelial cells at the level of single-gene expression, molecular subtype, and 10 categories reflecting intratumoral transcriptional heterogeneity. We develop InteractPrint, which considers how cancer epithelial cell heterogeneity influences cancer-immune interactions. We use T cell InteractPrint to predict response to immune checkpoint inhibition (ICI) in two breast cancer clinical trials testing neoadjuvant anti-PD-1 therapy. T cell InteractPrint was predictive of response in both trials versus PD-L1 (AUC = 0.82, 0.83 vs. 0.50, 0.72). This resource enables additional high-resolution investigations of the breast TME.

New genetic insights into immunotherapy outcomes in gastric cancer via single-cell RNA sequencing and random forest model

OBJECTIVE

The high mortality rate of gastric cancer, traditionally managed through surgery, underscores the urgent need for advanced therapeutic strategies. Despite advancements in treatment modalities, outcomes remain suboptimal, necessitating the identification of novel biomarkers to predict sensitivity to immunotherapy. This study focuses on utilizing single-cell sequencing for gene identification and developing a random forest model to predict immunotherapy sensitivity in gastric cancer patients.

METHODS

Differentially expressed genes were identified using single-cell RNA sequencing (scRNA-seq) and gene set enrichment analysis (GESA). A random forest model was constructed based on these genes, and its effectiveness was validated through prognostic analysis. Further, analyses of immune cell infiltration, immune checkpoints, and the random forest model provided deeper insights.

RESULTS

High METTL1 expression was found to correlate with improved survival rates in gastric cancer patients (P = 0.042), and the random forest model, based on METTL1 and associated prognostic genes, achieved a significant predictive performance (AUC = 0.863). It showed associations with various immune cell types and negative correlations with CTLA4 and PDCD1 immune checkpoints. Experiments in vitro and in vivo demonstrated that METTL1 enhances gastric cancer cell activity by suppressing T cell proliferation and upregulating CTLA4 and PDCD1.

CONCLUSION

The random forest model, based on scRNA-seq, shows high predictive value for survival and immunotherapy sensitivity in gastric cancer patients. This study underscores the potential of METTL1 as a biomarker in enhancing the efficacy of gastric cancer immunotherapy.

Five-gene signature for the prediction of response to immune checkpoint inhibitors in patients with gastric and urothelial carcinomas

BACKGROUND

Ample evidence supports the potential of programmed death-ligand 1 (PD-L1) expression, detected by immunohistochemistry, as a predictive biomarker for immunotherapy in patients with advanced cancers. To predict the response to immune checkpoint inhibitors in patients with gastric and urothelial carcinomas, we aimed to replace PD-L1 combined positive score (CPS) with CD274 mRNA in the original four-gene signature and PD-L1 CPS model developed by us.

METHOD

We used quantitative real-time polymerase chain reaction (qRT-PCR) to measure the expression levels of five target genes in a cohort of 49 patients (33 with gastric cancer and 16 with urothelial carcinoma) who had received immunotherapy and whose therapeutic responses were available. The predictive performance was evaluated using R package maxstat.

RESULTS

Cutoff values of mRNA expression level were measured using the log-rank statistics for progression-free survival (PFS). Based on these cutoffs, immunotherapy responses were predicted and sorted into responder (n = 12, 24.5%) and non-responder (n = 37, 75.5%) groups. The median PFS values of predicted responders and non-responders were 14.8 months (95% confidence interval [CI]: 0-34.7) and 4.7 months (95% CI: 1.0-8.4, p = 0.02), respectively. Among the 12 predicted responders, 10 had microsatellite-stable tumors with a low tumor mutational burden. The actual clinical responses (complete and partial) were higher in the responder group than those in the non-responder group: 83.3% and 16.2%, respectively.

CONCLUSION

We modified a predictive biomarker for CD274 mRNA expression to predict the response to immunotherapy in patients with gastric or urothelial carcinomas.

Circ007071 Inhibits Unsaturated Fatty Acid Synthesis by Interacting with miR-103-5p to Enhance PPARγ Expression in the Dairy Goat Mammary Gland

Understanding more precisely the mechanisms controlling the metabolism of fatty acid in the mammary gland of dairy goats is essential for future improvements in milk quality. Particularly since recent data have underscored a key role for circular RNAs (circRNAs) in the mammary gland function, high-throughput sequencing technology was used to identify expression levels of circRNAs in the mammary tissue of dairy goats during early and peak lactation in the present study. Compared with early lactation, results demonstrated that the expression level of circ007071 during peak lactation was 12.02-fold up-regulated. Subsequent studies in goat mammary epithelial cells (GMECs) revealed that circ007071 stimulated the synthesis of triglycerides (TAG) and cholesterol, as well as increased the content of saturated fatty acids (C16:0 and C18:0). More importantly, using a double luciferase reporting system allowed us to detect the circ007071 sequence at a binding site of miR-103-5p, indicating that it targeted this miRNA. Overexpression of circ007071 significantly decreased the abundance of miR-103-5p and led to inhibition of TAG synthesis. In contrast, the abundance of peroxisome proliferator-activated receptor γ (PPARγ), a target gene of miR-103-5p, was reinforced with the overexpression of circ007071. Thus, we conclude that one key function of circ007071 in the regulation of milk fat synthesis is to attenuate the inhibitory effect of miR-103-5p on PPARγ via direct interactions with miRNA. As a result, the process of TAG and saturated fatty acid is able to proceed.