Comprehensive analysis of single-cell and bulk RNA-sequencing data identifies B cell marker genes signature that predicts prognosis and analysis of immune checkpoints expression in head and neck squamous cell carcinoma.

Recent studies have shown that B cells and the associated tertiary lymphoid structures (TLS) correlate with the response of patients to immune checkpoint inhibitors (ICIs) and predict overall survival (OS) in cancer patients. We screened 145 B cell marker genes (BCMG) by a comprehensive analysis of single-cell RNA-sequencing (scRNA-seq) data of head and neck squamous cell carcinoma (HNSC) from the Gene Expression Omnibus (GEO) database. The BCMG signature (BCMGS) was established using The Cancer Genome Atlas (TCGA) dataset of HNSC and verified in four independent datasets. The multivariate Cox regression analysis identified the signature as an independent prognostic factor. A prognostic nomogram was constructed with independent prognostic factors using the TCGA dataset. GO and KEGG analysis revealed the underlying signaling pathways related to this signature. Study of immune profiles showed that patients in the low-risk group presented discriminative immune-cell infiltrations. Furthermore, the low-risk group was featured by higher TCR and BCR diversity, which suggested that low-risk patients may be more sensitive to ICIs. Immunohistochemistry was performed, and we found that high expression of FTH1 was significantly correlated with poor OS (P = 0.025). The expression of TIM-3, LAG-3 and PD-1 was positively correlated and associated with better OS in HNSC. However, there was no statistically significant difference between PD-L1, PD-L2, CTLA-4, TIGIT and prognosis. The BCMGS was a promising prognostic biomarker in HNSC, which may help to interpret the responses to immunotherapy and provide a new perspective for future research on the treatment in HNSC.

Validating a Macrophage Marker Gene Signature (MMGS) in Lung Adenocarcinoma Prognosis and Response to Immunotherapy.

Lung adenocarcinoma (LUAD) is the leading cause of cancer-related death worldwide. Tumor-associated macrophages play pivotal roles in the tumor microenvironment (TME) and prognosis of LUAD. We first used single-cell RNA sequencing data to identify macrophage marker genes in LUAD. Univariate, least absolute shrinkage and selection operator and stepwise multivariate Cox regression analyses were conducted to evaluate macrophage marker genes as prognostic factors and to construct the macrophage marker genes signature (MMGS). A novel 8-gene signature was constructed to predict prognosis based on 465 macrophage marker genes identified by an analysis of single-cell RNA sequencing data of LUAD, and was also verified in 4 independent GEO cohorts. The MMGS significantly classified patients into high-risk and low-risk groups in terms of OS. A prognostic nomogram based on independent risk factors was established to predict the 2-, 3- and 5-year survival, which indicated superior accuracy in predicting prognosis. The high-risk group was correlated to higher tumor mutational burden, number of neoantigens, T-cell receptor richness, and lower TIDE, which suggested that high-risk patients were more likely to benefit from immunotherapy. The prediction of the possibility of immunotherapy efficacy was also discussed. Analysis of an immunotherapy cohort further verified that patients with high-risk scores had better immunotherapy responses than low-risk patients. The MMGS is a promising signature for predicting prognosis and effectiveness of immunotherapy in patients with LUAD, and may be helpful for clinical decision-making.

Identification of a seven-lncRNAs panel that serves as a prognosis predictor and contributes to the malignant progression of laryngeal squamous cell carcinoma.

Background: Laryngeal squamous cell carcinoma (LSCC) is one of the most frequent head and neck cancers worldwide. Long non-coding RNAs (lncRNAs) play a critical role in tumorigenesis. However, the clinical significance of lncRNAs in LSCC remains largely unknown. Methods: In this study, transcriptome sequencing was performed on 107 LSCC and paired adjacent normal mucosa (ANM) tissues. Furthermore, RNA expression and clinical data of 111 LSCC samples were obtained from The Cancer Genome Atlas (TCGA) database. Bioinformatics analysis were performed to construct a model for predicting the overall survival (OS) of LSCC patients. Moreover, we investigated the roles of lncRNAs in LSCC cells through loss-of-function experiments. Results: A seven-lncRNAs panel including ENSG00000233397, BARX1-DT, LSAMP-AS1, HOXB-AS4, MNX1-AS1, LINC01385, and LINC02893 was identified. The Kaplan-Meier analysis demonstrated that the seven-lncRNAs panel was significantly associated with OS (HR:6.21 [3.27-11.81], p-value<0.0001), disease-specific survival (DSS) (HR:4.34 [1.83-10.26], p-value=0.0008), and progression-free interval (PFI) (HR:3.78 [1.92-7.43], p-value=0.0001). ROC curves showed the seven-lncRNAs panel predicts OS with good specificity and sensitivity. Separately silencing the seven lncRNAs inhibited the proliferation, migration, and invasion capacity of LSCC cells. Conclusion: Collectively, this seven-lncRNAs panel is a promising signature for predicting the prognosis of LSCC patients, and these lncRNAs could serve as potential targets for LSCC treatment.

The impact of the COVID-19 pandemic on palliative care practice: A survey of clinical oncologists.

Background: Palliative care is an essential intervention to improve the quality of life for patients with cancer, whereas the ongoing COVID-19 pandemic poses a challenge to supportive and palliative care providers. This survey aims to explore the current status of palliative care practice for cancer and the influence of COVID-19, from the perspective of oncologists. Methods: The semi-structure electronic questionnaire was designed. Mixed-mode surveys including electronic questionnaires, face-to-face interactions, and telephone interviews were adopted according to the willingness of respondents. Face-to-face and telephone interviews were based on same questions in the online questionnaire. Participants working in cancer-related departments with frontline palliative care experience during the COVID-19 outbreak were included. Surveys covered experiences and perspectives regarding the impact of COVID-19 on clinical work, personal lives, and palliative care practice. Suggestions on coping strategies were further proposed and qualitatively analyzed. Results: Thirty-seven oncologists participated in this study from September 2021 to January 2022. The majority of them believed COVID-19 significantly and negatively affected their clinical work routines (75.7%), personal daily lives (67.6%), and palliative care practice (64.9%). Most specialists considered that currently the palliative care system remained underdeveloped (73.0%), and other factors besides COVID-19 were associated with this situation (78.4%). Seventeen participants further made suggestions on how to promote palliative care during COVID-19, and three themes emerged through the qualitative analysis: (1) Remote or online service (88.2%); (2) Publicity, education, or shared decision-making for patients (29.4%); (3) Guidelines, training, or programs for care providers (23.6%). Conclusion: Oncologists consider that COVID-19 has an adverse impact on their palliative care practice and daily routine. In addition to COVID-19, other factors affecting palliative care should not be neglected. Corresponding measures are warranted to encourage palliative care practice during COVID-19.

The clinicopathological significance of PD-L1 expression assessed by the combined positive score (CPS) in head and neck squamous cell carcinoma.

The expression of programmed cell death-ligand 1 (PD-L1) is being used as a predictive biomarker for immunotherapy in head and neck squamous cell carcinoma (HNSCC). Our study was a retrospective cohort that assessed PD-L1 expression levels through immunohistochemistry (IHC) in 119 surgical specimens from HNSCC patients. The expression of PD-L1 was evaluated by IHC staining using the monoclonal antibody 22C3 (Dako) and the combined positive score (CPS). The relationship between the PD-L1 expression and clinicopathologic features was analyzed. 107 cases (89.9%) and 52 cases (43.7%) were positive for PD-L1 expression when the CPS cutoff value was set at 1 and 20 respectively. The tumor stage (P = 0.022) and tumor site (P = 0.004) were significantly correlated with the PD-L1 expression (CPS ≥ 1). Non-diabetic patients (P = 0.046) were corelated to positive PD-L1 expression (CPS ≥ 20). When evaluating PD-L1 expression in 40 laryngeal squamous cell carcinomas (LSC), the nodal stage was found to be significantly associated with high expression of PD-L1 (CPS ≥ 20) (P = 0.042). As for 36 patients with hypopharyngeal squamous cell carcinomas (HPSC), the positive PD-L1 expression (CPS ≥ 1) were typically younger (P = 0.030) and patients without type II diabetes (P = 0.040). We evaluated all possible clinical prognostic factors in the univariate Cox model, and there was no significant correlation between clinical characteristics and survival. The results of our findings may help to understand the association between the PD-L1 expression and clinicopathological characteristics, and it showed no significant correlation between the expression of PD-L1 and OS in HNSCC.

Pan-cancer analysis combined with experiments explores the oncogenic role of spindle apparatus coiled-coil protein 1 (SPDL1).

BACKGROUND: The function of spindle apparatus coiled-coil protein 1 (SPDL1) as a cancer-promoting gene has been reported in a number of studies. However, the pan-cancer analysis of SPDL1 is still lacking. Here, we performed this pan-cancer analysis to evaluate the expression and prognostic value of SPDL1 and gain insights into the association between SPDL1 and immune infiltration. METHODS: In this study, based on the datasets of The cancer genome atlas (TCGA), Gene expression omnibus (GEO), The Genotype-Tissue Expression (GTEx) and Clinical Proteomic Tumor Analysis Consortium (CPTAC), we used R4.1.0 software and the online tools, including TIMER2.0, GEPIA2, cBioPortal, Modbase, UALCAN, MEXPRESS, STRING, Ensembl, NCBI, HPA, Oncomine, PhosphoNET and the Kaplan-Meier plotter, to explore the potential oncogenic roles of SPDL1. The expression of SPDL1 was also further verified by immunohistochemistry (IHC) in lung adenocarcinoma (LUAD) tissues. RESULTS: SPDL1 was overexpressed in most tumors compared with adjacent normal tissues, and SPDL1 expression was significantly correlated with the prognosis in most tumor types. The main type of genetic mutation of SPDL1 was missense mutation and the frequency of R318Q/W mutation was highest (4/119). The expression of SPDL1 was closely associated with genomic instability. The SPDL1 phosphorylation levels in S555 was enhanced in ovarian cancer. The SPDL1 expression was positively correlated with the immune infiltration of CD8+ T-cells and cancer-associated fibroblasts (CAFs) in most of the tumor types. Nuclear division, organelle fission and chromosome segregation were involved in the functional mechanisms of SPDL1. CONCLUSIONS: These findings suggested that SPDL1 might serve as a biomarker for poor prognosis and immune infiltration in cancers, shedding new light on therapeutics of cancers.