Endometrial cancer (UCEC) is one of three major malignant tumors in women. The HOX gene regulates tumor development. However, the potential roles of HOX in the expression mechanism of multiple cell types and in the development and progression of tumor microenvironment (TME) cell infiltration in UCEC remain unknown. In this study, we utilized both the The Cancer Genome Atlas (TCGA) database and International Cancer Genome Consortium (ICGC) database to analyze transcriptome data of 529 patients with UCEC based on 39 HOX genes, combing clinical information, we discovered HOX gene were a pivotal factor in the development and progression of UCEC and in the formation of TME diversity and complexity. Here, a new scoring system was developed to quantify individual HOX patterns in UCEC. Our study found that patients in the low HOX score group had abundant anti-tumor immune cell infiltration, good tumor differentiation, and better prognoses. In contrast, a high HOX score was associated with blockade of immune checkpoints, which enhances the response to immunotherapy. The Real-Time quantitative PCR (RT-qPCR) and Immunohistochemistry (IHC) exhibited a higher expression of the HOX gene in the tumor patients. We revealed that the significant upregulation of the HOX gene in the epithelial cells can activate signaling pathway associated with tumour invasion and metastasis through single-cell RNA sequencing (scRNA-seq), such as nucleotide metabolic proce and so on. Finally, a risk prognostic model established by the positive relationship between HOX scores and cancer-associated fibroblasts (CAFs) can predict the prognosis of individual patients by scRNA-seq and transcriptome data sets. In sum, HOX gene may serve as a potential biomarker for the diagnosis and prediction of UCEC and to develop more effective therapeutic strategies.

BACKGROUND: Cancer-associated fibroblasts (CAFs) play a crucial role in the progression of colorectal cancer (CRC). However, the impact of CAF subpopulation trajectory differentiation on CRC remains unclear.
METHODS: In this study, we first explored the trajectory differences of CAFs subpopulations using bulk and integrated single-cell sequencing data, and then performed consensus clustering of CRC samples based on the trajectory differential genes of CAFs subpopulations. Subsequently, we analyzed the heterogeneity of CRC subtypes using bioinformatics. Finally, we constructed relevant prognostic signature using machine learning and validated them using spatial transcriptomic data.
RESULTS: Based on the differential genes of CAFs subpopulation trajectory differentiation, we identified two CRC subtypes (C1 and C2) in this study. Compared to C1, C2 exhibited worse prognosis, higher immune evasion microenvironment and high CAF characteristics. C1 was primarily associated with metabolism, while C2 was primarily associated with cell metastasis and immune regulation. By combining 101 combinations of 10 machine learning algorithms, we developed a High-CAF risk signatures (HCAFRS) based on the C2 characteristic gene. HCAFRS was an independent prognostic factor for CRC and, when combined with clinical parameters, significantly predicted the overall survival of CRC patients. HCAFRS was closely associated with epithelial-mesenchymal transition, angiogenesis, and hypoxia. Furthermore, the risk score of HCAFRS was mainly derived from CAFs and was validated in the spatial transcriptomic data.
CONCLUSIONS: In conclusion, HCAFRS has the potential to serve as a promising prognostic indicator for CRC, improving the quality of life for CRC patients.

Cancer incidence and mortality are increasing and impacting global life expectancy. Metabolic reprogramming in the tumor microenvironment (TME) is intimately related to tumorigenesis, progression, metastasis and drug resistance. Tumor cells drive metabolic reprogramming of other cells in the TME through metabolic induction of cytokines and metabolites, and metabolic substrate competition. Consequently, this boosts tumor cell growth by providing metabolic support and facilitating immunosuppression and angiogenesis. The metabolic interplay in the TME presents potential therapeutic targets. Here, we focus on the metabolic reprogramming of four principal cell subsets in the TME: CAFs, TAMs, TILs and TECs, and their interaction with tumor cells. We also summarize medications and therapies targeting these cells\' metabolic pathways, particularly in the context of immune checkpoint blockade therapy.

UNASSIGNED: Cancer-associated fibroblasts (CAFs) within the tumor microenvironment (TME) can interact with tumor parenchymal cells to promote tumor growth and migration. Fibroblast activation protein (FAP) expressed by CAFs can be targeted with positron emission tomography (PET) tracers, but studies on FAP expression patterns in intracranial tumors remain scarce. We aimed to evaluate FAP expression patterns in intracranial tumors with gallium-68 FAP inhibitor-04 (68Ga-FAPi-04) and immunohistochemical staining and to observe the interactions between CAFs and tumor cells with a head-to-head comparison of 68Ga-FAPi-04 and fluoride-18 fluoroethyl-L-tyrosine (18F-FET) for PET quantification analysis.
UNASSIGNED: We prospectively enrolled 22 adult patients with intracranial mass lesions. 68Ga-FAPi-04 and 18F-FET PET-computed tomography (PET/CT) brain imaging were applied before surgery. Maximal tumor-to-brain ratio (TBRmax), metabolic tumor volume (MTV), and total lesion tracer uptake (TLU) was obtained, and different thresholds were used for 68Ga-FAPi-04-positive lesion delineation owing to the lack of relevant guidelines. The MTV and TLU ratios of both tracers were calculated. Linear regression was applied to observe the differential efficacy of semiquantitative PET parameters.
UNASSIGNED: A total of 22 patients with a mean age of 50±13 years (range, 27-69 years) were enrolled. Heterogeneous patterns of 68Ga-FAPi-04 uptake [median of maximal standardized uptake value (SUVmax) =3.8; range, 0.1-19.1] were found. More malignant tumors, including brain metastasis, glioblastoma, and medulloblastoma, generally exhibited more significant 68Ga-FAPi-04 uptake than did the less malignant tumors, while the SUVmax and TBRmax exhibited nonsignificant differences across three intracranial lesion groups of primary brain tumor, brain metastasis, and noncancerous disease (SUVmax: P=0.092; TBRmax: P=0.189). Immunohistochemistry staining showed different stromal FAP expression status in various intracranial lesions. In 15 patients with positive 68Ga-FAPi-04 intracranial tumor uptake, the MTVFAPi:MTVFET ratio had differential efficacy in various types of intracranial tumors [95% confidence interval (CI): 0.572-7.712; P=0.027], and further quantification analyses confirmed the differential ability of the MTVFAPi:MTVFET ratio (95% CI: -0.045 to 11.013, P=0.052; 95% CI: 0.044-17.903, P=0.049; 95% CI: -1.131 to 30.596, P=0.065) with different isocontour volumetric thresholds.
UNASSIGNED: This head-to-head study demonstrated heterogeneous FAP expression in intracranial tumors. The FAP expression volume percentage in tumor parenchyma may therefore offer benefit with respect to differentiating between intracranial tumor types.

UNASSIGNED: Chimeric antigen receptor (CAR) T-cells have emerged as a ground-breaking therapy for the treatment of hematological malignancies due to their capacity for rapid tumor-specific killing and long-lasting tumor immunity. However, the same success has not been observed in patients with solid tumors. Largely, this is due to the additional challenges imposed by safe and uniform target selection, inefficient CAR T-cell access to sites of disease and the presence of a hostile immunosuppressive tumor microenvironment.
UNASSIGNED: Literature was reviewed on the PubMed database from the first description of a CAR by Kuwana, Kurosawa and colleagues in December 1987 through to the present day. This literature indicates that in order to tackle solid tumors, CAR T-cells can be further engineered with additional armoring strategies that facilitate trafficking to and infiltration of malignant lesions together with reversal of suppressive immune checkpoints that operate within solid tumor lesions.
UNASSIGNED: In this review, we describe a number of recent advances in CAR T-cell technology that set out to combat the problems imposed by solid tumors including tumor recruitment, infiltration, immunosuppression, metabolic compromise, and hypoxia.

BACKGROUND: Over the last two decades, tumor-derived RNA expression signatures have been developed for the two most commonly diagnosed tumors worldwide, namely prostate and breast tumors, in order to improve both outcome prediction and treatment decision-making. In this context, molecular signatures gained by main components of the tumor microenvironment, such as cancer-associated fibroblasts (CAFs), have been explored as prognostic and therapeutic tools. Nevertheless, a deeper understanding of the significance of CAFs-related gene signatures in breast and prostate cancers still remains to be disclosed.
METHODS: RNA sequencing technology (RNA-seq) was employed to profile and compare the transcriptome of CAFs isolated from patients affected by breast and prostate tumors. The differentially expressed genes (DEGs) characterizing breast and prostate CAFs were intersected with data from public datasets derived from bulk RNA-seq profiles of breast and prostate tumor patients. Pathway enrichment analyses allowed us to appreciate the biological significance of the DEGs. K-means clustering was applied to construct CAFs-related gene signatures specific for breast and prostate cancer and to stratify independent cohorts of patients into high and low gene expression clusters. Kaplan-Meier survival curves and log-rank tests were employed to predict differences in the outcome parameters of the clusters of patients. Decision-tree analysis was used to validate the clustering results and boosting calculations were then employed to improve the results obtained by the decision-tree algorithm.
RESULTS: Data obtained in breast CAFs allowed us to assess a signature that includes 8 genes (ITGA11, THBS1, FN1, EMP1, ITGA2, FYN, SPP1, and EMP2) belonging to pro-metastatic signaling routes, such as the focal adhesion pathway. Survival analyses indicated that the cluster of breast cancer patients showing a high expression of the aforementioned genes displays worse clinical outcomes. Next, we identified a prostate CAFs-related signature that includes 11 genes (IL13RA2, GDF7, IL33, CXCL1, TNFRSF19, CXCL6, LIFR, CXCL5, IL7, TSLP, and TNFSF15) associated with immune responses. A low expression of these genes was predictive of poor survival rates in prostate cancer patients. The results obtained were significantly validated through a two-step approach, based on unsupervised (clustering) and supervised (classification) learning techniques, showing a high prediction accuracy (≥ 90%) in independent RNA-seq cohorts.
CONCLUSIONS: We identified a huge heterogeneity in the transcriptional profile of CAFs derived from breast and prostate tumors. Of note, the two novel CAFs-related gene signatures might be considered as reliable prognostic indicators and valuable biomarkers for a better management of breast and prostate cancer patients.

BACKGROUND: The cyclin D1-cyclin dependent kinases (CDK)4/6 inhibitor palbociclib in combination with endocrine therapy shows remarkable efficacy in the management of estrogen receptor (ER)-positive and HER2-negative advanced breast cancer (BC). Nevertheless, resistance to palbociclib frequently arises, highlighting the need to identify new targets toward more comprehensive therapeutic strategies in BC patients.
METHODS: BC cell lines resistant to palbociclib were generated and used as a model system. Gene silencing techniques and overexpression experiments, real-time PCR, immunoblotting and chromatin immunoprecipitation studies as well as cell viability, colony and 3D spheroid formation assays served to evaluate the involvement of the G protein-coupled estrogen receptor (GPER) in the resistance to palbociclib in BC cells. Molecular docking simulations were also performed to investigate the potential interaction of palbociclib with GPER. Furthermore, BC cells co-cultured with cancer-associated fibroblasts (CAFs) isolated from mammary carcinoma, were used to investigate whether GPER signaling may contribute to functional cell interactions within the tumor microenvironment toward palbociclib resistance. Finally, by bioinformatics analyses and k-means clustering on clinical and expression data of large cohorts of BC patients, the clinical significance of novel mediators of palbociclib resistance was explored.
RESULTS: Dissecting the molecular events that characterize ER-positive BC cells resistant to palbociclib, the down-regulation of ERα along with the up-regulation of GPER were found. To evaluate the molecular events involved in the up-regulation of GPER, we determined that the epidermal growth factor receptor (EGFR) interacts with the promoter region of GPER and stimulates its expression toward BC cells resistance to palbociclib treatment. Adding further cues to these data, we ascertained that palbociclib does induce pro-inflammatory transcriptional events via GPER signaling in CAFs. Of note, by performing co-culture assays we demonstrated that GPER contributes to the reduced sensitivity to palbociclib also facilitating the functional interaction between BC cells and main components of the tumor microenvironment named CAFs.
CONCLUSIONS: Overall, our results provide novel insights on the molecular events through which GPER may contribute to palbociclib resistance in BC cells. Additional investigations are warranted in order to assess whether targeting the GPER-mediated interactions between BC cells and CAFs may be useful in more comprehensive therapeutic approaches of BC resistant to palbociclib.

mTORC1 is aberrantly activated in renal cell carcinoma (RCC) and is targeted by rapalogs. As for other targeted therapies, rapalogs clinical utility is limited by the development of resistance. Resistance often results from target mutation, but mTOR mutations are rarely found in RCC. As in humans, prolonged rapalog treatment of RCC tumorgrafts (TGs) led to resistance. Unexpectedly, explants from resistant tumors became sensitive both in culture and in subsequent transplants in mice. Notably, resistance developed despite persistent mTORC1 inhibition in tumor cells. In contrast, mTORC1 became reactivated in the tumor microenvironment (TME). To test the role of the TME, we engineered immunocompromised recipient mice with a resistance mTOR mutation (S2035T). Interestingly, TGs became resistant to rapalogs in mTORS2035T mice. Resistance occurred despite mTORC1 inhibition in tumor cells and could be induced by coculturing tumor cells with mutant fibroblasts. Thus, enforced mTORC1 activation in the TME is sufficient to confer resistance to rapalogs. These studies highlight the importance of mTORC1 inhibition in nontumor cells for rapalog antitumor activity and provide an explanation for the lack of mTOR resistance mutations in RCC patients.

BACKGROUND: Cancer-associated fibroblasts (CAFs) and their secretion, C-X-C motif chemokine ligand 12 (CXCL12), play an important role in the development of lung adenocarcinoma (LUAD). Interleukin 17A (IL-17A) is also crucial in regulating tumor progression. Herein, we explored the specific relationships between these two factors and their mechanisms in the progression of LUAD.
METHODS: Immunohistochemistry was utilized to assess the differential expression levels of IL-17A and CXCL12 in tumor versus normal tissues of LUAD patients, followed by gene correlation analysis. Cell counting kit-8 (CCK8), wound-healing and transwell assays were performed to investigate the effect of IL-17A on the function of LUAD cells. qPCR, immunofluorescence, immunohistochemistry and western blot analyses were conducted to elucidate the potential mechanism by which IL-17A facilitates the development of LUAD via CXCL12. Male BALB-C nude mice were used to explore the role of IL-17A in subcutaneous LUAD mouse models.
RESULTS: Elevated expression levels of IL-17A and CXCL12 were observed in LUAD tissues, exhibiting a positive correlation. Further studies revealed that IL-17A could stimulate CAFs to enhance the release of CXCL12, thereby facilitating the growth, proliferation, and metastasis of LUAD. The binding of CXCL12 to its specific receptor influences the activation of the Wnt/β-Catenin pathway, which in turn affects the progression of LUAD. In vivo experiments have demonstrated that IL-17A enhances the growth of LUAD tumors by facilitating the secretion of CXCL12. Conversely, inhibiting CXCL12 has been demonstrated to impede tumor growth.
CONCLUSIONS: We discovered that IL-17A promotes the release of CAFs-derived CXCL12, which in turn facilitates the development of LUAD via the Wnt/β-Catenin signaling pathway.

The tumor microenvironment (TME) plays an essential role in tumor progression and in modulating tumor response to anticancer therapy. Cellular senescence leads to a switch in the cell secretome, characterized by the senescence-associated secretory phenotype (SASP), which may regulate tumorigenesis. Senolytic therapy is considered a novel anticancer strategy that eliminates the deleterious effects of senescent cells in the TME. Here, we show that two different types of senolytic drugs, despite efficiently depleting senescent cells, have opposite effects on cancer-associated fibroblasts (CAFs) and their ability to regulate epithelial-mesenchymal transition (EMT). We found that senolytic drugs, navitoclax and the combination of dasatinib/quercetin, reduced the number of spontaneously senescent and TNF-induced senescent CAFs. Despite the depletion of senescent cells, the combination of dasatinib/quercetin versus navitoclax increased the secretion of the SASP pro-inflammatory cytokine IL-6. This differential effect correlated with the promotion of enhanced migration and EMT in MC38 colorectal cancer cells. Our results demonstrate that some senolytics may have side effects unrelated to their senolytic activity and may promote tumorigenesis. We argue for more careful and extensive studies of the effects of senolytics on various aspects of tumor progression and tumor resistance to therapy before the senolytic strategy is implemented in the clinic.