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.

Nomogram for predicting the prognosis of metastatic colorectal cancer patients treated with anti-PD1 therapy based on serum lipids analysis.

BACKGROUND: Serum lipids have been identified to be used as prognostic biomarkers in several types of cancer. The primary objective of this study was to evaluate the prognostic value of serum lipids in metastatic colorectal cancer (mCRC) patients received anti-PD-1 therapy. METHODS: Pretreatment and the alteration of serum lipids, including apolipoprotein B (ApoB), apolipoprotein A-I (ApoA-I), cholesterol (CHO), high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol (LDL-C) and triglyceride (TG) after 2 courses of anti-PD1 therapy, were collected. Kaplan-Meier survival and cox regression analysis were performed to identify the prognostic values on overall survival (OS). Finally, those significant predictors from multivariate analysis were used to construct a nomogram for the prediction of prognosis. RESULTS: Baseline ApoB, CHO, HDL-C, LDL-C and early changes of ApoB, ApoA-I, HDL-C were statistically significant in the ROC analysis, showing good discriminatory ability in terms of OS. In multivariate analysis, treatment lines, lung metastasis, baseline HDL-C (low vs. high, HR, 6.30; 95% CI 1.82-21.80; P = 0.004) and early changes in HDL-C (reduction vs. elevation, HR, 4.59, 95% CI 1.20-17.63; P = 0.026) independently predicted OS. The area under the time-dependent ROC curve at 1 year, 2 years and 3 years consistently demonstrated the satisfactory accuracy and predictive value of the nomogram (AUC: 0.88, 0.85, 0.84). CONCLUSION: Overall, high level at baseline and an early elevation of HDL-C are correlated with better outcomes in mCRC patients treated with anti-PD1 therapy. The constructed nomogram indicated that the factors are strong predictive markers for response and prognosis to anti-PD-1 therapy in metastatic colorectal cancer.

Baseline and early changes in the neutrophil-lymphocyte ratio (NLR) predict survival outcomes in advanced colorectal cancer patients treated with immunotherapy.

BACKGROUND: Systemic inflammation plays a role in carcinogenesis and is related to overall survival in patients with different cancer types, including those treated with immune checkpoint blockade (ICB). The neutrophil-lymphocyte ratio (NLR) is calculated by circulating neutrophil to lymphocyte counts, which represents an indicator of the balance between the deleterious roles of neutrophilia and the beneficial roles of lymphocyte-mediated immunity. We hypothesized that the NLR may predict outcomes in metastatic colorectal cancer (mCRC) patients treated with immunotherapy. MATERIALS AND METHODS: This retrospective study included 110 mCRC patients who were treated with immunotherapy at Sun Yat-sen University Cancer Center. Several inflammatory biomarkers were measured at baseline and after two cycles of treatment. The X-tile program was used to obtain the cutoff values. We examined the impact of both baseline and posttreatment inflammatory index levels on overall survival (OS). RESULTS: In univariate analysis, both a low baseline NLR (P = 0.014) and a decreased NLR after 2 cycles of immunotherapy (P < 0.001) were considerably correlated with better OS. In multivariate analysis, age, liver metastasis, baseline lymphocyte-monocyte ratio (LMR), baseline NLR and early changes in NLR independently predicted OS. Patients with both a low baseline NLR and an early NLR reduction had the longest OS (median, 29.63 months). The best outcomes were remarkably observed in patients who had both an early NLR reduction and a high tumor mutational burden (TMB) (≥10 mut/Mb) (P < 0.0001). CONCLUSIONS: Both a low baseline NLR and an early NLR reduction are significantly associated with a better prognosis in mCRC patients treated with immunotherapy. Further analysis indicated that the combination of NLR and TMB could obtain additional predictive power.

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.