The relevant mechanism of tumor-associated macrophages (TAMs) in the treatment of colorectal cancer patients with immune checkpoint inhibitors (ICIs) is discussed, and the application prospects of TAMs in reversing the treatment tolerance of ICIs are discussed to provide a reference for related studies. As a class of drugs widely used in clinical tumor immunotherapy, ICIs can act on regulatory molecules on cells that play an inhibitory role - immune checkpoints - and kill tumors in the form of an immune response by activating a variety of immune cells in the immune system. The sensitivity of patients with different types of colorectal cancer to ICI treatment varies greatly. The phenotype and function of TAMs in the colorectal cancer microenvironment are closely related to the efficacy of ICIs. ICIs can regulate the phenotypic function of TAMs, and TAMs can also affect the tolerance of colorectal cancer to ICI therapy. TAMs play an important role in ICI resistance, and making full use of this target as a therapeutic strategy is expected to improve the immunotherapy efficacy and prognosis of patients with colorectal cancer.

Breast cancer is the most common cause of death from cancer in women. Here, we present the case of a 43-year-old woman, who received a diagnosis of claudin-low luminal B breast cancer. The lesion revealed to be a poorly differentiated high-grade infiltrating ductal carcinoma, which was strongly estrogen receptor (ER)/progesterone receptor (PR) positive and human epidermal growth factor receptor (HER2) negative. Her tumor underwent in-depth chromosomal, mutational and gene expression analyses. We found a pathogenic protein truncating mutation in the TP53 gene, which is predicted to disrupt its transcriptional activity. The patient also harbors germline mutations in some mismatch repair (MMR) genes, and her tumor displays the presence of immune infiltrates, high tumor mutational burden (TMB) status and the apolipoprotein B mRNA editing enzyme catalytic polypeptide 3 (APOBEC3) associated signatures, which, overall, are predictive for the use of immunotherapy. Here, we propose promising prognostic indicators as well as potential therapeutic strategies based on the molecular characterization of the tumor.

Cellular senescence, a novel hallmark of cancer, is associated with patient outcomes and tumor immunotherapy. However, at present, there is no systematic study on the use of cellular senescence-related long non-coding RNAs (CSR-lncRNAs) to predict survival in patients with osteosarcoma. In this study, we aimed to identify a CSR-lncRNAs signature and to evaluate its potential use as a survival prognostic marker and predictive tool for immune response of osteosarcoma.

We downloaded a cohort of patients with osteosarcoma from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. We performed differential expression and co-expression analyses to identify CSR-lncRNAs. We performed univariate and multivariate Cox regression analyses along with the random forest algorithm to identify lncRNAs significantly correlated with senescence. Subsequently, we assessed the predictive models using survival curves, receiver operating characteristic curves, nomograms, C-index, and decision curve analysis. Based on this model, patients with osteosarcoma were divided into two groups according to their risk scores. Then, using Gene Ontology and Kyoto Encyclopedia of Genes and Genomes analyses, we compared their clinical characteristics to uncover functional differences. We further conducted immune infiltration analyses using estimation of stromal and immune cells in malignant tumor tissues using expression data (ESTIMATE), cell-type identification by estimating relative subsets of rna transcripts (CIBERSORT), and single-sample gene set enrichment analysis for the two groups. We also evaluated the expression of the target genes of immune checkpoint inhibitors (ICIs).

We identified six lncRNAs that were significantly correlated with senescence and accordingly established a novel cellular senescence-related lncRNA prognostic signature incorporating these lncRNAs. The nomogram indicated that the risk model was an independent prognostic factor that could predict the survival of patients with osteosarcoma. This model demonstrated high accuracy upon validation. Further analysis revealed that patients with osteosarcoma in the low-risk group exhibited better clinical outcomes and enhanced immune infiltration.

The six-CSR-lncRNA prognostic signature effectively predicted survival outcomes and patients in the low-risk group might have improved immune infiltration.

Chronic Obstructive Pulmonary Disease (COPD) is a heterogeneous, chronic inflammatory process of the lungs and, like other complex diseases, is caused by both genetic and environmental factors. Detailed understanding of the molecular mechanisms of complex diseases requires the study of the interplay among different biomolecular layers, and thus the integration of different omics data types. In this study, we investigated COPD-associated molecular mechanisms through a correlation-based network integration of lung tissue RNA-seq and DNA methylation data of COPD cases (n = 446) and controls (n = 346) derived from the Lung Tissue Research Consortium. First, we performed a SWIM-network based analysis to build separate correlation networks for RNA-seq and DNA methylation data for our case-control study population. Then, we developed a method to integrate the results into a coupled network of differentially expressed and differentially methylated genes to investigate their relationships across both molecular layers. The functional enrichment analysis of the nodes of the coupled network revealed a strikingly significant enrichment in Immune System components, both innate and adaptive, as well as immune-system component communication (interleukin and cytokine-cytokine signaling). Our analysis allowed us to reveal novel putative COPD-associated genes and to analyze their relationships, both at the transcriptomics and epigenomics levels, thus contributing to an improved understanding of COPD pathogenesis.

Although immune checkpoint inhibitors have revolutionized the treatment of several advanced solid cancers, in colorectal cancer, the transformative benefit of these innovative medicines is currently limited to those with deficient mismatch repair or high microsatellite instability. Tumor mutational burden (TMB) has emerged as a potential predictor of immunotherapy benefit, but the lack of standardization in its assessment and reporting has hindered the introduction of this biomarker in routine clinical practice. Here, we compiled 45 colorectal cancer studies utilizing numerical thresholds for high-TMB. In this group of studies, TMB cut-offs ranged from 6.88 to 41 mut/Mb and were most often set at 10, 17, or 20 mut/Mb. Additionally, we observed divergent TMB definitions and inconsistent disclosure of specific methodological details, which collectively emphasize the substantial lack of harmonization within the field. Ongoing efforts to harmonize TMB assessment will be critical to validate TMB as a predictive marker of immunotherapy response.