Integrated analysis of single-cell and bulk RNA sequencing data reveals a myeloid cell-related regulon predicting neoadjuvant immunotherapy response across cancers.

BACKGROUND: Immunotherapy has brought about a paradigm shift in the treatment of cancer. However, the majority of patients exhibit resistance or become refractory to immunotherapy, and the underlying mechanisms remain to be explored. METHODS: Sing-cell RNA sequencing (scRNA­seq) datasets derived from 1 pretreatment and 1 posttreatment achieving pathological complete response (pCR) patient with lung adenocarcinoma (LUAD) who received neoadjuvant immunotherapy were collected, and pySCENIC was used to find the gene regulatory network (GRN) between cell types and immune checkpoint inhibitor (ICI) response. A regulon predicting ICI response was identified and validated using large­scale pan-cancer data, including a colorectal cancer scRNA­seq dataset, a breast cancer scRNA­seq dataset, The Cancer Genome Atlas (TCGA) pan-cancer cohort, and 5 ICI transcriptomic cohorts. Symphony reference mapping was performed to construct the myeloid cell map. RESULTS: Thirteen major cluster cell types were identified by comparing pretreatment and posttreatment patients, and the fraction of myeloid cells was higher in the posttreatment group (19.0% vs. 11.8%). A PPARG regulon (containing 23 target genes) was associated with ICI response, and its function was validated by a colorectal cancer scRNA­seq dataset, a breast cancer scRNA­seq dataset, TCGA pan-cancer cohort, and 5 ICI transcriptomic cohorts. Additionally, a myeloid cell map was developed, and cluster I, II, and III myeloid cells with high expression of PPARG were identified. Moreover, we constructed a website called PPARG ( https://pparg.online/PPARG/ or http://43.134.20.130:3838/PPARG/ ), which provides a powerful discovery tool and resource value for researchers. CONCLUSIONS: The PPARG regulon is a predictor of ICI response. The myeloid cell map enables the identification of PPARG subclusters in public scRNA-seq datasets and provides a powerful discovery tool and resource value.

Choline metabolism reprogramming mediates an immunosuppressive microenvironment in non-small cell lung cancer (NSCLC) by promoting tumor-associated macrophage functional polarization and endothelial cell proliferation.

INTRODUCTION: Lung cancer is a prevalent malignancy globally, and immunotherapy has revolutionized its treatment. However, resistance to immunotherapy remains a challenge. Abnormal cholinesterase (ChE) activity and choline metabolism are associated with tumor oncogenesis, progression, and poor prognosis in multiple cancers. Yet, the precise mechanism underlying the relationship between ChE, choline metabolism and tumor immune microenvironment in lung cancer, and the response and resistance of immunotherapy still unclear. METHODS: Firstly, 277 advanced non-small cell lung cancer (NSCLC) patients receiving first-line immunotherapy in Sun Yat-sen University Cancer Center were enrolled in the study. Pretreatment and the alteration of ChE after 2 courses of immunotherapy and survival outcomes were collected. Kaplan-Meier survival and cox regression analysis were performed, and nomogram was conducted to identify the prognostic and predicted values. Secondly, choline metabolism-related genes were screened using Cox regression, and a prognostic model was constructed. Functional enrichment analysis and immune microenvironment analysis were also conducted. Lastly, to gain further insights into potential mechanisms, single-cell analysis was performed. RESULTS: Firstly, baseline high level ChE and the elevation of ChE after immunotherapy were significantly associated with better survival outcomes for advanced NSCLC. Constructed nomogram based on the significant variables from the multivariate Cox analysis performed well in discrimination and calibration. Secondly, 4 choline metabolism-related genes (MTHFD1, PDGFB, PIK3R3, CHKB) were screened and developed a risk signature that was found to be related to a poorer prognosis. Further analysis revealed that the choline metabolism-related genes signature was associated with immunosuppressive tumor microenvironment, immune escape and metabolic reprogramming. scRNA-seq showed that MTHFD1 was specifically distributed in tumor-associated macrophages (TAMs), mediating the differentiation and immunosuppressive functions of macrophages, which may potentially impact endothelial cell proliferation and tumor angiogenesis. CONCLUSION: Our study highlights the discovery of ChE as a prognostic marker in advanced NSCLC, suggesting its potential for identifying patients who may benefit from immunotherapy. Additionally, we developed a prognostic signature based on choline metabolism-related genes, revealing the correlation with the immunosuppressive microenvironment and uncovering the role of MTHFD1 in macrophage differentiation and endothelial cell proliferation, providing insights into the intricate workings of choline metabolism in NSCLC pathogenesis.

Levels of pretreatment serum lipids predict responses to PD-1 inhibitor treatment in advanced intrahepatic cholangiocarcinoma.

BACKGROUND: It has been identified that serum lipids can be used as prognostic biomarkers in several types of cancer and are associated with patient survival. We aimed to clarify the prognostic value of the serum lipids and to establish a novel effective nomogram for overall survival (OS) in intrahepatic cholangiocarcinoma (iCCA) patients receiving anti-PD1 therapy. METHODS: Pretreatment serum lipids were retrospectively analyzed for prognostic value, including apolipoprotein B (APOB), apolipoproteinA-1 (APOA1), total cholesterol (TC), high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol (LDL-C) and triglycerides (TG), which were assessed for prediction accuracy using Kaplan-Meier survival curves and time-dependent receiver operating characteristic (ROC). Cox regression analysis with univariate and multivariate factors was used to identify prognostic factors predictive of OS, and prognostic nomograms were constructed. RESULTS: All the serum lipids showed good discriminatory ability in terms of OS (all P < 0.05), the higher the lipid levels, the better the prognosis, while APOA1 and TG were remarkable independent predictors for OS in multivariate analysis (hazard ratio, 2.177,2.035; confidence interval, 1.393-3.402, 1.184-3.498; P = 0.001, P = 0.01). Four (CA19-9, APOA1, tumor number and TG) independent prognostic factors were chosen to generate the nomogram for OS. The area under the ROC curve at 1-year and 2-year consistently demonstrated that the predictive value of the nomogram was superior to serum lipids. CONCLUSION: In our study, serum lipid levels were used as a prognostic nomogram in the prediction of anti-PD-1 therapy efficacy in patients with iCCA.

Sarcopenia defined by skeletal muscle mass index at the third lumbar vertebra is a prognostic factor for extensive-stage small cell lung cancer patients: a retrospective study.

Background: Small cell lung cancer (SCLC) is one of the most aggressive types of lung cancer and reliable indicators are needed for improved patient management. The evaluation of skeletal muscle index of the third lumbar vertebra (L3MI) based on computed tomography (CT) is used to estimate patient prognosis in multiple cancers. However, its function in extensive-stage SCLC remains controversial. Considering that the maintenance of muscle mass may affect the survival of cancer patients. Herein, a retrospective study was conducted to investigate whether sarcopenia defined by skeletal muscle mass index at the third lumbar vertebra is a prognostic factor in extensive-stage SCLC cancer patients. Methods: This retrospective analysis included extensive-stage SCLC patients diagnosed at the Sun Yat-sen University Cancer Center from January 2009 to March 2017 with platinum-based chemotherapy. Clinical data were collated for further examination, and CT or positron emission tomography (PET)/CT datasets were analyzed for body mass index (BMI) and L3MI. Follow-up data were collected by contacting patients or their families. Overall survival (OS) was defined as the interval between the date of treatment started and the date of death or censoring. The Kaplan-Meier product limit method and log-rank tests were used to assess differences in OS between the high L3MI and low L3MI groups. Cox regression analysis was used to identify independent factors of OS. Results: For the 139 extensive-stage SCLC patients, the median follow-up time was 26.1 months (range, 0.4 to 79.4 months). The median OS was 9.5 months. There were no differences in age, inflammatory factors, nor progression after first-line treatment between the high L3MI and low L3MI groups. Kaplan-Meier analysis showed that the OS of the high L3MI group was significantly longer than that of the low L3MI group (14.045 vs. 9.985 months; P=0.007), and multivariate analysis identified high L3MI to be an independent prognostic factor for predicting longer OS in extensive-stage SCLC patients [hazard ratio (HR), 0.623; 95% confidence interval (CI), 0.405-0.960; P=0.032]. Conclusions: Sarcopenia defined by L3MI is a prognostic factor for extensive-stage SCLC patients and early intervention of muscle mass maintaining may achieve better cancer management.

The genetic alteration spectrum of the SWI/SNF complex: The oncogenic roles of BRD9 and ACTL6A.

SWItch/Sucrose NonFermentable (SWI/SNF) is a set of multi-subunits chromatin remodeling complexes, playing important roles in a variety of biological processes. Loss-of-function mutations in the genes encoding SWI/SNF subunits have been reported in more than 20% of human cancers. Thus, it was widely considered as a tumor suppressor in the past decade. However, recent studies reported that some genes encoding subunits of SWI/SNF complexes were amplified and play oncogenic roles in human cancers. In present study, we summarized the genetic alteration spectrum of SWI/SNF complexes, and firstly systematically estimated both the copy number variations and point mutations of all 30 genes encoding the subunits in this complex. Additionally, the bioinformatics analyses were performed for two significantly amplified genes, ACTL6A and BRD9, to investigate their oncogenic roles in human cancers. Our findings may lay a foundation for the discovery of potential treatment targets in SWI/SNF complexes of cancers.