Artificial neural network systems to predict the response to sintilimab in squamous-cell non-small-cell lung cancer based on data of ORIENT-3 study.

Background: Existing biomarkers and models for predicting response to programmed cell death protein 1 monoclonal antibody in advanced squamous-cell non-small cell lung cancer (sqNSCLC) did not have enough accuracy. We used data from the ORIENT-3 study to construct artificial neural network (ANN) systems to predict the response to sintilimab for sqNSCLC.

Methods: Four ANN systems based on bulk RNA data to predict disease control (DC), immune DC (iDC), objective response (OR) and immune OR (iOR) were constructed and tested for patients with sqNSCLC treated with sintilimab.

Spatial analyses revealed CXCL5 and SLC6A14 as the markers of microvascular invasion in intrahepatic cholangiocarcinoma.

Background: Microvascular invasion (MVI) is a critical prognostic factor in intrahepatic cholangiocarcinoma (ICC), strongly associated with postoperative recurrence. However, the phenotypic features and spatial organization of MVI remain inadequately understood.

Methods: We performed a spatial transcriptomic analysis on 29,632 spots from six ICC samples, manually delineating MVI clusters using the cloupe software.

DKK1+ tumor cells inhibited the infiltration of CCL19+ fibroblasts and plasma cells contributing to worse immunotherapy response in hepatocellular carcinoma.

Intra-tumor immune infiltration plays a pivotal role in the interaction with tumor cells in hepatocellular carcinoma (HCC). However, its phenotype and related spatial structure remained elusive. To address these limitations, we conducted a comprehensive study combining spatial data (38,191 spots from eight samples) and single-cell data (56,022 cells from 20 samples).

The co-location of MARCO+ tumor-associated macrophages and CTSE+ tumor cells determined the poor prognosis in intrahepatic cholangiocarcinoma.

Intra-tumor immune infiltration is a crucial element interacting with tumor cells in intrahepatic cholangiocarcinoma (ICC). However, its phenotype and related spatial structure remained elusive. To address these limitations, we undertook a comprehensive study combining spatial data (29,632 spots from six samples) and single-cell data (21,158 cells from 35 samples).

Spatial analyses revealed S100P + TFF1 + tumor cells in spread through air spaces samples correlated with undesirable therapy response in non-small cell lung cancer.

Spread through air spaces (STAS) is a recognized aggressive pattern in lung cancer, serving as a crucial risk factor for postoperative recurrence. However, its phenotype and related spatial structure have remained elusive. To address these limitations, we conducted a comprehensive study based on spatial data, analyzing over 30,000 spots from 14 non-STAS samples and one STAS sample.

Multi-omics analysis and response prediction of PD-1 monoclonal antibody containing regimens in patients with relapsed/refractory diffuse large B-cell lymphoma.

Patients with relapsed/refractory (r/r) diffuse large B-cell lymphoma (DLBCL) show varied responses to PD-1 monoclonal antibody (mAb) containing regimens. The mechanisms and predictive biomarkers for the efficacy of this regimen are unclear. This study retrospectively collected r/r DLBCL patients who received PD-1 mAb and rituximab regimens as salvage therapy.

Mechanism exploration and model construction for small cell transformation in EGFR-mutant lung adenocarcinomas.

Small-cell lung cancer (SCLC) transformation accounts for 3-14% of resistance in EGFR-TKI relapsed lung adenocarcinomas (LUADs), with unknown molecular mechanisms and optimal treatment strategies. We performed transcriptomic analyses (including bulk and spatial transcriptomics) and multiplex immunofluorescence on pre-treated samples from LUADs without transformation after EGFR-TKI treatment (LUAD-NT), primary SCLCs (SCLC-P) and LUADs with transformation after EGFR-TKI treatment (before transformation: LUAD-BT; after transformation: SCLC-AT). Our study found that LUAD-BT exhibited potential transcriptomic characteristics for transformation compared with LUAD-NT.

Mutational variant allele frequency profile as a biomarker of response to immune checkpoint blockade in non-small cell lung Cancer.

Introduction: Identifying new biomarkers for predicting immune checkpoint inhibitors (ICIs) response in non-small cell lung cancer (NSCLC) is crucial. We aimed to assess the variant allele frequency (VAF)-related profile as a novel biomarker for NSCLC personalized therapy.

Methods: We utilized genomic data of 915 NSCLC patients via cBioPortal and a local cohort of 23 patients for model construction and mutational analysis.

Single-cell and spatial transcriptomics reveal a high glycolysis B cell and tumor-associated macrophages cluster correlated with poor prognosis and exhausted immune microenvironment in diffuse large B-cell lymphoma.

Background: Diffuse large B-cell lymphoma (DLBCL) is a heterogeneous malignancy characterized by varied responses to treatment and prognoses. Understanding the metabolic characteristics driving DLBCL progression is crucial for developing personalized therapies.

Methods: This study utilized multiple omics technologies including single-cell transcriptomics (n = 5), bulk transcriptomics (n = 966), spatial transcriptomics (n = 10), immunohistochemistry (n = 34), multiple immunofluorescence (n = 20) and to elucidate the metabolic features of highly malignant DLBCL cells and tumor-associated macrophages (TAMs), along with their associated tumor microenvironment.

Single-cell and spatial analyses revealed the co-location of cancer stem cells and SPP1+ macrophage in hypoxic region that determines the poor prognosis in hepatocellular carcinoma.

In hepatocellular carcinoma (HCC), classical cancer stem cells (CSC) markers were shared by normal stem cells, targeting which may hinder hepatic regeneration and cause liver failure. Additionally, the spatial structure of CSC still remained elusive. To address these limitations, we undertook a comprehensive study combining single-cell data (56,022 cells from 20 samples) and spatial data (38,191 spots from eight samples) to obtain CSC signature and uncover its spatial structure.

Identification of novel prognostic autoantibodies in diffuse large B-cell lymphoma treated with rituximab plus cyclophosphamide, doxorubicin, vincristine, and prednisone via a high-throughput antigen microarray.

Background: R-CHOP (rituximab plus cyclophosphamide, doxorubicin, vincristine, and prednisone) is a standard first-line treatment for diffuse large B-cell lymphoma (DLBCL). However, 20%-40% of patients survive less than 5 years. Novel prognostic biomarkers remain in demand.

An immunosuppressive subtype of senescent tumor cells predicted worse immunotherapy response in lung adenocarcinoma.

Senescent tumor cells (STCs) can induce immunosuppression, promoting tumor progression and therapy resistance. However, the specific characteristics of immunosuppressive STC have not been thoroughly investigated. This study aimed to characterize and elucidate the immunosuppressive phenotype of STC in lung adenocarcinoma by employing single-cell and bulk transcriptomics, as well as serum proteomics profiling.

Low TP53 variant allele frequency as a biomarker for anti-programmed death (ligand) 1 monotherapy in lung adenocarcinoma.

Background: TP53 mutation heterogeneity should be considered when using TP53 as a predictive biomarker for anti-programmed death (ligand) 1 (PD-(L)1) monotherapy in lung adenocarcinoma (LUAD). However, whether TP53 variant allele frequency (VAF) should also be considered remains unknown.

Methods: Patients with LUAD from both published research and the local cohort were included to discover and validate the relationship between TP53 VAF and the efficacy of PD-(L)1 inhibitors.

Front-line therapy for brain metastases and non-brain metastases in advanced epidermal growth factor receptor-mutated non-small cell lung cancer: a network meta-analysis.

Background: The brain is a common metastatic site in patients with non-small cell lung cancer (NSCLC), resulting in a relatively poor prognosis. Systemic therapy with epidermal growth factor receptor (EGFR)-tyrosine kinase inhibitors (TKIs) is recommended as the first-line treatment for EGFR -mutated, advanced NSCLC patients. However, intracranial activity varies in different drugs.

Incidence, survival comparison, and novel prognostic evaluation approaches for stage iii-iv pulmonary large cell neuroendocrine carcinoma and small cell lung cancer.

Background: Pulmonary large cell neuroendocrine carcinoma (LCNEC) and small cell lung cancer (SCLC) are two types of high-grade neuroendocrine carcinomas of the lung with poor prognosis. LCNEC has not been thoroughly studied due to its rarity, data are also lacking regarding the survival comparison and prognosis analysis of patients with locally advanced or metastatic LCNEC and SCLC.

Methods: Data of patients with LCNEC, SCLC, and other NSCLC who were diagnosed from 1975 to 2019 were extracted from the Surveillance, Epidemiology and End Results (SEER) database to estimate incidence.

Integrative analyses of bulk and single-cell RNA-seq identified cancer-associated fibroblasts-related signature as a prognostic factor for immunotherapy in NSCLC.

An emerging view regarding cancer-associated fibroblast (CAF) is that it plays a critical role in tumorigenesis and immunosuppression in the tumor microenvironment (TME), but the clinical significance and biological functions of CAFs in non-small cell lung cancer (NSCLC) are still poorly explored. Here, we aimed to identify the CAF-related signature for NSCLC through integrative analyses of bulk and single-cell genomics, transcriptomics, and proteomics profiling. Using CAF marker genes identified in weighted gene co-expression network analysis (WGCNA), we constructed and validated a CAF-based risk model that stratifies patients into two prognostic groups from four independent NSCLC cohorts.

Multiomics analysis revealed the mechanisms related to the enhancement of proliferation, metastasis and EGFR-TKI resistance in EGFR-mutant LUAD with ARID1A deficiency.

Introduction: Dysregulated ARID1A expression is frequently detected in lung adenocarcinoma (LUAD) and mediates significant changes in cancer behaviors and a poor prognosis. ARID1A deficiency in LUAD enhances proliferation and metastasis, which could be induced by activation of the Akt signaling pathway. However, no further exploration of the mechanisms has been performed.

Analysis on methylation and expression of and its correlation with immunity and immunotherapy in lung adenocarcinoma.

To find biomarkers for immunity and immunotherapy in lung adenocarcinoma (LUAD) through multiomics analysis. The multiomics data of patients with LUAD were downloaded from the TCGA and GEO databases. CIBERSORT, quanTIseq, ESTIMATEScore, k-means clustering, gene set enrichment analysis, gene set variation analysis, immunophenoscore and logistic regression were used in this study.

Evolutionary Characteristics and Immunologic Divergence of Lung and Brain Metastasis Lesions in NSCLC.

Unlabelled: Brain metastases (BM) is one of the main reasons for lung cancer-related deaths but lack prediction methods. Many patients with BMs do not benefit from immunotherapy. A comprehensive genomic analysis of matched primary tumors (PT) and their BM lesions may provide new insight into the evolutionary and immune characteristics.

Integrated molecular characterization of esophageal basaloid squamous cell carcinoma: a subtype with distinct RNA expression pattern and immune characteristics, but no specific genetic mutations.

Esophageal basaloid squamous cell carcinoma (bSCC) is a subtype of squamous cell carcinoma (SCC) with a different behavior and poor prognosis. Exploring bSCC's molecular characteristics and treatment strategies are of great clinical significance. We performed multi-omics analysis of paired bSCC and common SCC (cSCC) using whole exome sequencing and a NanoString nCounter gene expression panel.

DLX2 Is a Potential Immune-Related Prognostic Indicator Associated with Remodeling of Tumor Microenvironment in Lung Squamous Cell Carcinoma: An Integrated Bioinformatical Analysis.

Background: It is still an unmet clinical need to identify potent biomarkers for immunotherapy on patients with lung squamous cell carcinoma (LUSC).

Methods: In this study, we explored the differentially expressed genes (DEGs) that were simultaneously correlated with four pathways (i.e.

ARID1A deficiency reverses the response to anti-PD(L)1 therapy in EGFR-mutant lung adenocarcinoma by enhancing autophagy-inhibited type I interferon production.

Introduction: EGFR mutations in non-small cell lung cancer (NSCLC) are associated with a poor response to immune checkpoint inhibitors (ICIs), and only 20% of NSCLC patients harboring EGFR mutations benefit from immunotherapy. Novel biomarkers or therapeutics are needed to predict NSCLC prognosis and enhance the efficacy of ICIs in NSCLC patients harboring EGFR mutations, especially lung adenocarcinoma (LUAD) patients, who account for approximately 40-50% of all NSCLC cases.

Methods: An ARID1A-knockdown (ARID1A-KD) EGFR-mutant LUAD cell line was constructed using lentivirus.