BackgroundThe role of tumor-associated macrophages (TAMs) in determining the outcome between the antitumor effects of the adaptive immune system and the tumor’s anti-immunity stratagems, is controversial. Macrophages modulate their activities and phenotypes by integration of signals in the tumor microenvironment. Depending on how macrophages are activated, they may adopt so-called M1-like, antitumor or M2-like, protumor profiles. In many solid tumors, a dominance of M2-like macrophages is associated with poor outcomes but in some tumor types, strong M1-like profiles are linked to better outcomes. We aimed to investigate the interrelationship of these TAM populations to establish how they modulate the efficacy of the adaptive immune system in early lung cancer.MethodsMacrophages from matched lung (non-tumor-associated macrophages (NTAMs)) and tumor samples (TAMs) from resected lung cancers were assessed by bulk and single-cell transcriptomic analysis. Protein expression of genes characteristic of M1-like (chemokine (C-X-C motif) ligand 9) or M2-like (matrix metallopeptidase 12) functions was confirmed by confocal microscopy. Immunohistochemistry related the distribution of TAM transcriptomic signatures to density of CD8+ tissue-resident memory T cells (TRM) in tumors and survival data from an independent cohort of 393 patients with lung cancer.ResultsTAMs have significantly different transcriptomic profiles from NTAMs with >1000 differentially expressed genes. TAMs displayed a strong M2-like signature with no significant variation between patients. However, single-cell RNA-sequencing supported by immuno-stained cells revealed that additionally, in 25% of patients the M2-like TAMs also co-expressed a strong/hot M1-like signature (M1hot). Importantly, there was a strong association between the density of M1hot TAMs and TRM cells in tumors that was in turn linked to better survival. Our data suggest a mechanism by which M1hot TAMs may recruit TRM cells via CXCL9 expression and sustain them by making available more of the essential fatty acids on which TRM depend.ConclusionsWe showed that in early lung cancer, expression of M1-like and M2-like gene signatures are not mutually exclusive since the same TAMs can simultaneously display both gene-expression profiles. The presence of M1hot TAMs was associated with a strong TRM tumor-infiltrate and better outcomes. Thus, therapeutic approaches to re-program TAMs to an M1hot phenotype are likely to augment the adaptive antitumor responses.

Stratification of patients for targeted and immune-based therapies requires extensive genomic profiling that enables sensitive detection of clinically relevant variants and interrogation of biomarkers, such as tumor mutational burden (TMB) and microsatellite instability (MSI). Detection of single and multiple nucleotide variants, copy number variants, MSI, and TMB was evaluated using a commercially available next-generation sequencing panel containing 523 cancer-related genes (1.94 megabases). Analysis of formalin-fixed, paraffin-embedded tissue sections and cytologic material from 45 tumor samples showed that all previously known MSI-positive samples (n Z 7), amplifications (n Z 9), and pathogenic variants (n Z 59) could be detected. TMB and MSI scores showed high intralaboratory and interlaboratory reproducibility (eight samples tested in 11 laboratories). For reliable TMB analysis, 20 ng DNA was shown to be sufficient, even for relatively poor-quality samples. A minimum of 20% neoplastic cells was required to minimize variations in TMB values induced by chromosomal instability or tumor heterogeneity. Subsequent analysis of 58 consecutive lung cancer samples in a diagnostic setting was successful and revealed sufficient somatic mutations to generate mutational signatures in 14 cases. In conclusion, the 523-gene assay can be applied for evaluation of multiple DNA-based biomarkers relevant for treatment selection.

Whole-brain radiotherapy (WBRT) is the treatment backbone for many patients with brain metastasis; however, its efficacy in preventing disease progression and the associated toxicity have questioned the clinical impact of this approach and emphasized the need for alternative treatments. Given the limited therapeutic options available for these patients and the poor understanding of the molecular mechanisms underlying the resistance of metastatic lesions to WBRT, we sought to uncover actionable targets and biomarkers that could help to refine patient selection. Through an unbiased analysis of experimental in vivo models of brain metastasis resistant to WBRT, we identified activation of the S100A9–RAGE–NF-κB–JunB pathway in brain metastases as a potential mediator of resistance in this organ. Targeting this pathway genetically or pharmacologically was sufficient to revert the WBRT resistance and increase therapeutic benefits in vivo at lower doses of radiation. In patients with primary melanoma, lung or breast adenocarcinoma developing brain metastasis, endogenous S100A9 levels in brain lesions correlated with clinical response to WBRT and underscored the potential of S100A9 levels in the blood as a noninvasive biomarker. Collectively, we provide a molecular framework to personalize WBRT and improve its efficacy through combination with a radiosensitizer that balances therapeutic benefit and toxicity.

MicroRNAs are known to regulate important pathways in asthma pathology including the IL-6 and IFN pathways. MicroRNAs have been found not only within cells but also within extracellular vesicles such as exosomes. In this study, we particularly focused on microRNA cargo of nanovesicles in bronchoalveolar lavage of severe asthmatic patients. We extracted nanovesicle RNA using a serial filtration method. RNA content was analyzed with small RNA sequencing and mapped to pathways affected using WebGestalt 2017 Software. We report that severe asthma patients have deficient loading of microRNAs into their airway luminal nanovesicles and an altered profile of small RNA nanovesicle content (i.e., ribosomal RNA and broken transcripts, etc.). This decrease in microRNA cargo is predicted to increase the expression of genes by promoting inflammation and remodeling. Consistently, a network of microRNAs was associated with decreased FEV1 and increased eosinophilic and neutrophilic inflammation in severe asthma. MicroRNAs in airway nanovesicles may, thus, be valid biomarkers to define abnormal biological disease processes in severe asthma and monitor the impact of interventional therapies.