Increasing evidence supports that the immune infiltration of tumours is associated with prognosis. Here, we sought to assess the relevance of the cellular composition of the immune infiltrate to survival after platinum-based chemotherapy amongst patients with high-grade serous ovarian cancer and evaluate these effects by molecular subtype. We searched publicly available databases and identified 13 studies with more than 2000 patients. We estimated the proportions of 22 immune cell subsets by using a computational approach (CIBERSORT). Then, we investigated the associations between each immune cell subset and progression-free survival (PFS) and overall survival (OS), with cellular proportions modelled as quartiles. A high fraction of M1 [hazard ratio (HR) = 0.92, 95% confidence interval (CI) = 0.86-0.99] and M0 (HR = 0.93, 95% CI = 0.87-0.99) macrophages emerged as the most closely associated with favourable OS. Neutrophils were associated with poor OS (HR = 1.06, 95% CI = 1.00-1.13) and PFS (HR = 1.10, 95% CI = 1.02-1.13). Amongst the immunoreactive tumours, the M0 macrophages and the CD8+ T cells were associated with improved OS, whereas the M2 macrophages conferred worse OS. Interestingly, PD-1 was associated with good OS (HR=0.89, 95% CI = 0.80-1.00) and PFS (HR=0.89, 95% CI = 0.79-1.01) in this subtype. Four subgroups of tumours with distinct survival patterns were identified using immune cell proportions with unsupervised clustering. Further investigations of the quantitative cellular immune infiltrations in tumours may contribute to therapeutic advances.

The tumor immune microenvironment (TIME) is likely an important determinant of sensitivity to immune checkpoint inhibitor (ICI) treatment. However, a comprehensive analysis covering the complexity and diversity of the TIME and its influence on ICI therapeutic efficacy is still lacking. Data from 782 samples from 10 ICI clinical trials were collected. To infer the infiltration of 22 subsets of immune cells, CIBERSORTx was applied to the bulk tumor transcriptomes. The associations between each cell fraction and the response to ICI treatment, progression-free survival (PFS) and overall survival (OS) were evaluated, modeling cellular proportions as quartiles. Activity of the interferon-γ pathway, the cytolytic activity score and the MHC score were associated with good prognosis in melanoma. Of the immune cells investigated, M1 macrophages, activated memory CD4⁺ T cells, T follicular helper (Tfh) cells and CD8⁺ T cells correlated with response and prolonged PFS and OS, while resting memory CD4⁺ T cells was associated with unfavorable prognosis in melanoma and urothelial cancer. Consensus clustering revealed four immune subgroups with distinct responses to ICI therapy and survival patterns. The cluster with high proportions of infiltrated CD8⁺ T cells, activated memory CD4⁺ T cells, and Tfh cells and low levels of resting memory CD4⁺ T cells exhibited a higher tumor mutation burden and neoantigen load in melanoma and conferred a higher probability of response and improved survival. Local systemic immune cellular differences were associated with outcomes after ICI therapy. Further investigations of the tumor-infiltrating cellular immune response will lay the foundation for achieving durable efficacy.

The gut microbiota may have an effect on the therapeutic resistance and toxicity of immune checkpoint inhibitors (ICIs). However, the associations between the highly variable genomes of gut bacteria and the effectiveness of ICIs remain unclear, despite the fact that merely a few gene mutations between similar bacterial strains may cause significant phenotypic variations. Here, using datasets from the gut microbiome of 996 patients from seven clinical trials, we systematically identify microbial genomic structural variants (SVs) using SGV-Finder. The associations between SVs and response, progression-free survival, overall survival, and immune-related adverse events are systematically explored by metagenome-wide association analysis and replicated in different cohorts. Associated SVs are located in multiple species, including Akkermansia muciniphila, Dorea formicigenerans, and Bacteroides caccae. We find genes that encode enzymes that participate in glucose metabolism be harbored in these associated regions. This work uncovers a nascent layer of gut microbiome heterogeneity that is correlated with hosts’ prognosis following ICI treatment and represents an advance in our knowledge of the intricate relationships between microbiota and tumor immunotherapy.

The immune infiltration profiles of the tumor microenvironment have effects on the prognosis of head and neck squamous cell carcinoma (HNSCC). Whereas, HNSCC is a heterogeneous group of tumors, but past work has not taken this into consideration. Herein, we investigate the associations between survival and the function of immune cells in different tumorigenic sites of HNSCC. 1149 samples of HNSCC were collected from publicly accessible databases. Based on gene expression data, CIBERSORTx was applied to determine the proportion of 22 immune cell subpopulations. In the Cox regression model, the associations between overall survival, disease-free survival, and immune cells were examined, modeling gene expression and immune cell proportion as quartiles. Consensus cluster analysis was utilized to uncover immune infiltration profiles. Regardless of tumor sites, CD8+ T cells and activated CD4 memory T cells were associated with favorable survival, while eosinophils were the opposite. The survival of the hypopharynx, oral cavity, and larynx subsites was somewhat affected by immune cells, while the survival of the oropharynx subsite potentially was the most impacted. High expression of TIGIT, CIITA, and CXCR6 was linked to better survival, mainly in the oropharynx subsite. Immune cell clusters with four distinct survival profiles were discovered, of which the cluster with a high CD8+ T cell content had a better prognosis. The immune-infiltration pattern is related to the survival of HNSCC to varying degrees depending on the tumor sites; forthcoming studies into immune-mediated infiltration profiles will lay the groundwork for treating HNSCC with precision therapy.

Tumor-infiltrating immune cells (TIICs) play a critical role in breast cancer (BC) prognosis, but little is known regarding the efficacy of endocrine therapy in patients with ER-positive BC with diverse immunological phenotypes. To investigate whether TIICs affect survival after endocrine therapy in patients with different BC molecular subtypes, data were gathered from six studies totaling 1900 samples. CIBERSORTx was used to analyze the invasion of 22 immune cell subpopulations using a bulk gene expression profile. The relationships of immune-related metagenes and immune cell subsets with survival (distant metastasis-free survival, relapse-free survival, and overall survival) were studied using Cox regression models with cell proportions modeled in quartiles. The immune score and IGHG3 and LCK gene activity were linked to a better prognosis. Among the immune cells, monocytes, resting CD4+ memory T cells and plasma cells were correlated with prolonged survival, while neutrophils, Tregs, M0 macrophages, and M2 macrophages were associated with an unfavorable prognosis. Similar effects were reported for the luminal A subtype. In the luminal B subtype, γδ T cells and eosinophils were favorable prognostic factors. Covariate-adjusted multivariate Cox regression analysis revealed that high proportions of resting CD4+ memory T cells and resting dendritic cells were correlated with a good prognosis. Meanwhile, neutrophils were associated with an unfavorable prognosis. Understanding how monocytes and macrophages interact in the tumor microenvironment may be a promising study focus. Comprehensive research on the cellular immune response in tumors could help facilitate the development of new treatments.

Background: The purpose of this study is to develop an effective but concise long non-coding RNA (lncRNA) expression signature that can predict response to neoadjuvant chemotherapy for breast cancer (BC) patients. Methods: lncRNA expression profiling in 1102 BC patients from Gene Expression Omnibus datasets was analyzed using lncRNA-mining approach. The association between lncRNA signature and pathological complete response (pCR) was analyzed using logistic regression model in the training set (GSE25066, n = 488). Validation was performed in independent testing datasets, GSE20194, GSE20271, GSE22093, and GSE23988 (n = 614). Bonferroni method was employed for multiple testing corrections. Cell proliferation assay and Western blot assay were performed to evaluate the cell viability and protein expression level, respectively. Results: Three lncRNAs (AK291479, U79293, and BC032585) have been identified to be significantly associated with pCR in the training dataset (Bonferroni p-value < 0.05). Expression signature with these lncRNAs was predictive of pCR in the training (AUC = 0.74) and testing (AUC = 0.72) datasets. Weighted gene co-expression network analysis and gene functional annotation suggest that the three lncRNAs were involved in cell cycle process. To confirm the functional significance of the identified lncRNAs, BC032585 was selectively silenced using RNA interference. Knockdown of BC032585 lncRNA significantly promoted cell resistance to multiple anticancer-drugs through upregulating MDR1 expression in breast cancer cells. Conclusion: These results suggest that lncRNAs such as BC032585 might be involved in chemotherapeutic response in breast cancer patients, and the three-lncRNA signature identified in the present study may serve as a useful biomarker for the selection of responsive breast cancer patients in neoadjuvant chemotherapy.