Immunotherapy has revolutionized therapeutic patterns of small cell lung cancer (SCLC). Human leukocyte antigen class II (HLA class II) is related to antitumor immunity. However, the implications of HLA class II in SCLC remain incompletely understood.

Immunotherapy for malignant tumors has made great progress, but many patients do not benefit from it. The complex intratumoral heterogeneity (ITH) hindered the in-depth exploration of immunotherapy. Conventional bulk sequencing has masked intratumor complexity, preventing a more detailed discovery of the impact of ITH on treatment efficacy. Hence, we initiated this study to explore ITH at the multi-omics spatial level and to seek prognostic biomarkers of immunotherapy efficacy considering the presence of ITH.

Immunotherapy is considered a major breakthrough in the treatment of small cell lung cancer (SCLC), although its anti-tumor efficacy is limited. With a high degree of malignancy and high heterogeneity, SCLC is difficult to treat in the clinic. A new combination strategy is urgently needed to further improve the efficacy of immunotherapy in patients with SCLC. By immunofluorescence, 100 SCLC patients in a local cohort were classified into the SCLC-A (high ASCL1 expression; n = 36), SCLC-N (high NEUROD1 expression; n = 32), SCLC-P (high POU2F3 expression; n = 14), and SCLC-Y (high YAP1 expression; n = 18) subtypes. Each SCLC molecular subtype represented different prognoses, tumor microenvironment traits, and immunotherapy sensitivities. Analysis of both the local and public cohorts suggested that the SCLC-Y subtype exhibited the worst clinical outcome (p < 0.05) when compared with other subtypes. SCLC with high YAP1 expression was characterized by high PD-L1 expression, high stromal score, T-cell functional impairment, and a close relationship with immune-related pathways. YAP1 upregulated PD-L1 expression and suppressed T cell activation, thus leading to immune evasion. In in vitro experiments, blockade of YAP1 promoted cancer cell apoptosis, immune cell proliferation, T-cell activation, and cytotoxic T-cell infiltration, thus further potentiating the efficacy of immunotherapy in patients with the SCLC-Y subtype.

In the study, Methylated DNA immunoprecipitation sequencing, RNA sequencing, and whole-exome sequencing were employed to clinical small cell lung cancer (SCLC) patients. Then, we verified the therapeutic predictive effects of differentially methylated genes (DMGs) in 62 SCLC cell lines. Of 4552 DMGs between chemo-sensitive and chemo-insensitive group, coding genes constituted the largest percentage (85.08%), followed by lncRNAs (10.52%) and miRNAs (3.56%). Both two groups demonstrated two methylation peaks near transcription start site and transcription end site. Two lncRNA-miRNA-mRNA networks suggested the extensive genome connection between chemotherapy efficacy-related non-coding RNAs (ncRNAs) and mRNAs. Combing miRNAs and lncRNAs could effectively predict chemotherapy response in SCLC. In addition, we also verified the predictive values of mutated genes in SCLC cell lines. This study was the first to evaluate multiple drugs efficacy-related ncRNAs and mRNAs which were modified by methylation in SCLC. DMGs identified in our research might serve as promising therapeutic targets to reverse drugs-insensitivity by complex lncRNA-miRNA-mRNA mechanisms in SCLC.

Cancer immune function and tumor microenvironment are governed by long noncoding RNAs (lncRNAs). Nevertheless, it has yet to be established whether lncRNAs play a role in tumor-associated neutrophils (TANs). Here, a computing framework based on machine learning was used to identify neutrophil-specific lncRNA with prognostic significance in squamous cell carcinoma and lung adenocarcinoma using univariate Cox regression to comprehensively analyze immune, lncRNA, and clinical characteristics. The risk score was determined using LASSO Cox regression analysis. Meanwhile, we named this risk score as "TANlncSig." TANlncSig was able to distinguish between better and worse survival outcomes in various patient datasets independently of other clinical variables. Functional assessment of TANlncSig showed it is a marker of myeloid cell infiltration into tumor infiltration and myeloid cells directly or indirectly inhibit the anti-tumor immune response by secreting cytokines, expressing immunosuppressive receptors, and altering metabolic processes. Our findings highlighted the value of TANlncSig in TME as a marker of immune cell infiltration and showed the values of lncRNAs as indicators of immunotherapy.

Immunotherapies may prolong the survival of patients with small-cell lung cancer (SCLC) to some extent. The role of forkhead box protein P3 (FOXP3) in tumor microenvironment (TME) remains controversial. We aimed to examine FOXP3-related expression characteristics and prognostic values and to develop a clinically relevant predictive system for SCLC.

OX40 and OX40 ligand (OX40L), as essential immune checkpoint (IC) modulators, are highly correlated with cancer immunity regulation as well as tumor microenvironment (TME). Immunotherapy showed outstanding advantages in small-cell lung cancer (SCLC) therapy. However, functions and clinical significance of OX40 and OX40L in SCLC were not clear yet.

In recent years, immunotherapy has achieved notable success in cancer treatment. Indeed, the novel immune checkpoint lymphocyte activation gene-3 (LAG3) has shown promising therapeutic efficacy in non-small cell lung cancer. However, it is unclear about the role of LAG3 in immunotherapy and survival in small cell lung cancer (SCLC).

Pulmonary sarcomatoid carcinoma (PSC) is an uncommon subtype of lung cancer, and immune checkpoint blockade promises in clinical benefit. However, virtually nothing is known about the expression of common immune checkpoints in PSC. Here, we performed immunohistochemistry (IHC) to detect nine immune-related proteins in 97 PSC patients. Based on the univariable Cox regression, random forests were used to establish risk models for OS and DFS. Moreover, we used the GSEA, CIBERSORT, and ImmuCellAI to analyze the enriched pathways and microenvironment. Univariable analysis revealed that CD4 (P = 0.008), programmed cell death protein 1 (PD-1; P = 0.003), galectin-9 (Gal-9) on tumor cells (TCs; P = 0.021) were independent for DFS, while CD4 (P = 0.020), PD-1 (P = 0.004), Gal-9 (P = 0.033), and HLA on TILs (P = 0.031) were significant for OS. Meanwhile, the expression level of CD8 played a marginable role in DFS (P = 0.061), limited by the number of patients. The combination of Gal-9 on TC with CD4 and PD-1 on TILs demonstrated the most accurate prediction for DFS (AUC: 0.636-0.791, F1-score: 0.635-0.799), and a dramatic improvement to TNM-stage (P < 0.001 for F1-score of 1-y, 3-y, and 5-yDFS). A similar finding was also observed in the predictive ability of CD4 for OS (AUC: 0.602-0.678, F1-score: 0.635-0.679). CD4 was negatively associated with the infiltration of neutrophils (P = 0.015). PDCD1 (coding gene of PD-1) was positively correlated to the number of exhausted T cells (Texs; P = 0.020) and induced regulatory T cells (iTregs; P = 0.021), and LGALS9 (coding gene of Gal-9) was positively related to the level of dendritic cells (DCs; P = 0.021). Further, a higher combinational level of CD4, PDCD1 on TILs, and LAGLS9 on TCs were proved to be infiltrated with more M1-type macrophages (P < 0.05). We confirmed the expression status of nine immune-related proteins and established a TNM-Immune system for OS and DFS in PSC to assist clinical risk-stratification.

Advances in sequencing and imaging technologies offer a unique opportunity to unravel cell heterogeneity and develop new immunotherapy strategies for cancer research. There is an urgent need for a resource that effectively integrates a vast amount of transcriptomic profiling data to comprehensively explore cancer tissue heterogeneity and the tumor microenvironment. In this context, we developed the Single-cell and Spatially-resolved Cancer Resources (SCAR) database, a combined tumor spatial and single-cell transcriptomic platform, which is freely accessible at http://8.142.154.29/SCAR2023 or http://scaratlas.com. SCAR contains spatial transcriptomic data from 21 tumor tissues and single-cell transcriptomic data from 11 301 352 cells encompassing 395 cancer subtypes and covering a wide variety of tissues, organoids, and cell lines. This resource offers diverse functional modules to address key cancer research questions at multiple levels, including the screening of tumor cell types, metabolic features, cell communication and gene expression patterns within the tumor microenvironment. Moreover, SCAR enables the analysis of biomarker expression patterns and cell developmental trajectories. SCAR also provides a comprehensive analysis of multi-dimensional datasets based on 34 state-of-the-art omics techniques, serving as an essential tool for in-depth mining and understanding of cell heterogeneity and spatial location. The implications of this resource extend to both cancer biology research and cancer immunotherapy development.

The nervous system is one of the most complicated and enigmatic systems within the animal kingdom. Recently, the emergence and development of spatial transcriptomics (ST) and single-cell RNA sequencing (scRNA-seq) technologies have provided an unprecedented ability to systematically decipher the cellular heterogeneity and spatial locations of the nervous system from multiple unbiased aspects. However, efficiently integrating, presenting and analyzing massive multiomic data remains a huge challenge. Here, we manually collected and comprehensively analyzed high-quality scRNA-seq and ST data from the nervous system, covering 10 679 684 cells. In addition, multi-omic datasets from more than 900 species were included for extensive data mining from an evolutionary perspective. Furthermore, over 100 neurological diseases (e.g. Alzheimer's disease, Parkinson's disease, Down syndrome) were systematically analyzed for high-throughput screening of putative biomarkers. Differential expression patterns across developmental time points, cell types and ST spots were discerned and subsequently subjected to extensive interpretation. To provide researchers with efficient data exploration, we created a new database with interactive interfaces and integrated functions called the Spatiotemporal Cloud Atlas for Neural cells (SCAN), freely accessible at http://47.98.139.124:8799 or http://scanatlas.net. SCAN will benefit the neuroscience research community to better exploit the spatiotemporal atlas of the neural system and promote the development of diagnostic strategies for various neurological disorders.

Bromodomain-containing protein 9 (BRD9) is a specific subunit of the non-canonical SWI/SNF (ncBAF) chromatin-remodeling complex, whose function in human embryonic stem cells (hESCs) remains unclear. Here, we demonstrate that impaired BRD9 function reduces the self-renewal capacity of hESCs and alters their differentiation potential. Specifically, BRD9 depletion inhibits meso-endoderm differentiation while promoting neural ectoderm differentiation. Notably, supplementation of NODAL, TGF-β, Activin A or WNT3A rescues the differentiation defects caused by BRD9 loss. Mechanistically, BRD9 forms a complex with BRD4, SMAD2/3, β-CATENIN and P300, which regulates the expression of pluripotency genes and the activity of TGF-β/Nodal/Activin and Wnt signaling pathways. This is achieved by regulating the deposition of H3K27ac on associated genes, thus maintaining and directing hESC differentiation. BRD9-mediated regulation of the TGF-β/Activin/Nodal pathway is also demonstrated in the development of pancreatic and breast cancer cells. In summary, our study highlights the crucial role of BRD9 in the regulation of hESC self-renewal and differentiation, as well as its participation in the progression of pancreatic and breast cancers.

For small cell lung cancer (SCLC) therapy, immunotherapy might have unique advantages to some extent. Galectin-9 (Gal-9) plays an important role in antitumor immunity, while little is known of its function in SCLC.

Small-cell lung cancer (SCLC) has poor prognosis and is prone to drug resistance. It is necessary to search for possible influencing factors for SCLC chemotherapy insensitivity. Therefore, we proposed an mRNA network to track the chemotherapy insensitivity in SCLC.

It is a challenge to efficiently integrate and present the tremendous amounts of single-cell data generated from multiple tissues of various species. Here, we create a new database named SPEED for single-cell pan-species atlas in the light of ecology and evolution for development and diseases (freely accessible at http://8.142.154.29 or http://speedatlas.net). SPEED is an online platform with 4 data modules, 7 function modules and 2 display modules. The 'Pan' module is applied for the interactive analysis of single cell sequencing datasets from 127 species, and the 'Evo', 'Devo', and 'Diz' modules provide comprehensive analysis of single-cell atlases on 18 evolution datasets, 28 development datasets, and 85 disease datasets. The 'C2C', 'G2G' and 'S2S' modules explore intercellular communications, genetic regulatory networks, and cross-species molecular evolution. The 'sSearch', 'sMarker', 'sUp', and 'sDown' modules allow users to retrieve specific data information, obtain common marker genes for cell types, freely upload, and download single-cell datasets, respectively. Two display modules ('HOME' and 'HELP') offer easier access to the SPEED database with informative statistics and detailed guidelines. All in all, SPEED is an integrated platform for single-cell RNA sequencing (scRNA-seq) and single-cell whole-genome sequencing (scWGS) datasets to assist the deep-mining and understanding of heterogeneity among cells, tissues, and species at multi-levels, angles, and orientations, as well as provide new insights into molecular mechanisms of biological development and pathogenesis.

Hairtail (Trichiurus lepturus) is a kind of abundant marine fish, and its by-products contain rich protein resources, which can be better exploited and utilized in the food industry. In this study, the glycoprotein of hairtail by-products (GHB) was extracted using ultrasonic-assisted salt solution extraction with hairtail by-products as the raw material. The anti-fatigue effect of GHB was explored by mouse behavior experiments (shuttle box test, open field test and load swimming test). The results showed that the active escape times of the GHB group increased compared with the blank group in the shuttle box test, and the GHB group stayed in the central area for more time in the open field test. At the same time, the exhaustive swimming time of high-dose-group mice was 122.01% longer than that of the blank control group. GHB can improve the memory learning ability and activity of mice, and exert its anti-fatigue effect by eliminating excessive free radicals, slowing the metabolism of amino acids and proteins, and increasing glycogen reserves. This study provides a theoretical basis for the function mechanism of glycoprotein of hairtail by-products and the development of supplementary material in functional foods.