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Malignant cell growth is fueled by interactions between tumor cells and the stromal cells composing the tumor microenvironment. The human liver is a major site of tumors and metastases, but molecular identities and intercellular interactions of different cell types have not been resolved in these pathologies. Here, we apply single cell RNA‐sequencing and spatial analysis of malignant and adjacent non‐malignant liver tissues from five patients with cholangiocarcinoma or liver metastases. We find that stromal cells exhibit recurring, patient‐independent expression programs, and reconstruct a ligand–receptor map that highlights recurring tumor–stroma interactions. By combining transcriptomics of laser‐capture microdissected regions, we reconstruct a zonation atlas of hepatocytes in the non‐malignant sites and characterize the spatial distribution of each cell type across the tumor microenvironment. Our analysis provides a resource for understanding human liver malignancies and may expose potential points of interventions. SYNOPSIS Single cell transcriptomics and spatial methods are used to generate a cell atlas of the human liver tumor microenvironment, exposing recurring tumor‐stroma interactions and zonation patterns in the healthy and malignant tissue. A single cell atlas of the malignant and adjacent non‐malignant human liver is presented. Recurring stromal cell gene expression signatures are found in liver metastases and cholangiocarcinomas. Tumor and stromal cells communicate through a conserved ligand‐receptor interaction network. Spatial transcriptomics reveal zonated expression patterns in the malignant and non‐malignant liver. Graphical Abstract Single cell transcriptomics and spatial methods are used to generate a cell atlas of the human liver tumor microenvironment, exposing recurring tumor‐stroma interactions and zonation patterns in the healthy and malignant tissue.

Pancreatic ductal adenocarcinoma (PDAC) remains the most deadly disease worldwide, with the lowest survival rate among all cancer types. Recent evidence suggests that hyaluronan (HA), a major component of ECM, provides a favorable microenvironment for cancer progression. Pancreatic ductal adenocarcinoma is typically characterized by a dense desmoplastic stroma containing a large amount of HA. Accumulation of HA promotes tumor growth in mice and correlates with poor prognosis in patients with PDAC. Because HA is involved in various malignant behaviors of cancer (such as increased cell proliferation, migration, invasion, angiogenesis, and chemoresistance), inhibiting HA synthesis/signaling or depleting HA in tumor stroma could represent a promising therapeutic strategy against PDAC. In this review article, we summarize our current understanding of the role of HA in the progression of PDAC and discuss possible therapeutic approaches targeting HA. We summarize our current understanding of the role of hyaluronan in the progression of pancreatic ductal adenocarcinoma and discuss possible therapeutic approaches targeting HA.

Background The clinical significance of tumor-stroma ratio (TSR) has been examined in many tumors. Here we systematically reviewed all studies that evaluated TSR in head and neck cancer. Methods Four databases (Scopus, Medline, PubMed and Web of Science) were searched using the term tumo(u)r-stroma ratio. The preferred reporting items for systematic reviews and meta-analyses (PRISMA) were followed. Results TSR was studied in nine studies of different subsites (including cohorts of nasopharyngeal, oral, laryngeal and pharyngeal carcinomas). In all studies, TSR was evaluated using hematoxylin and eosin staining. Classifying tumors based on TSR seems to allow for identification of high-risk cases. In oral cancer, specifically, our meta-analysis showed that TSR is significantly associated with both cancer-related mortality (HR 2.10, 95%CI 1.56–2.84) and disease-free survival (HR 1.84, 95%CI 1.38–2.46). Conclusions The assessment of TSR has a promising prognostic value and can be implemented with minimum efforts in routine head and neck pathology.

Accurate predictions on prognosis and neoadjuvant therapy response are crucial for esophagogastric junction adenocarcinoma (EGJA) patients. Therefore, we aimed to investigate the predictive abilities of several indicators, including tumor stroma ratio (TSR), tumor stroma maturity (TSM), and the density and spatial distribution of tumor-infiltrating immune cells (TIICs), such as T cells, B cells, and tumor-associated macrophages (TAMs). Resection and biopsy specimens of a total of 695 patients were included, obtained from the National Cancer Center (NCC) and The Cancer Genome Atlas (TCGA) cohorts. TSR and TSM were evaluated based on histological assessment. TIICs were quantified by QuPath following immunohistochemical (IHC) staining in resection specimens, while the Klintrup–Mäkinen (KM) grade was employed for evaluating TIIC in biopsy specimens. Patients with high stromal levels or immature stroma had relatively worse prognoses. Furthermore, high CD8 + T cell count in the tumor periphery, as well as low CD68 + TAM count either in the tumor center or in the tumor periphery, was an independent favorable prognostic factor. Significantly, the combination model incorporating TSM and CD163 + TAMs emerged as an independent prognostic factor in both two independent cohorts (HR 3.644, 95% CI 1.341–9.900, p  = 0.011 and HR 1.891, 95% CI 1.195–2.99, p  = 0.006, respectively). Additionally, high stromal levels in preoperative biopsies correlated with poor neoadjuvant therapy response ( p  < 0.05). In conclusion, our findings suggest that TSR, TSM, CD8 + T cell, CD68 + TAMs, and CD163 + TAMs predict the prognosis to some extent in patients with EGJA. Notably, the combined model incorporating TSM and CD163 + TAM can contribute significantly to prognostic stratification. Additionally, high stromal levels evaluated in preoperative biopsy specimens correlated with poor neoadjuvant therapy response.

Gemcitabine/Cisplatin (Gem/Cis) chemotherapy is a standard treatment for muscle‐invasive bladder cancer (MIBC) but yields suboptimal response rates. The contribution of tumor‐stromal crosstalk and macrophage recruitment to chemoresistance remains poorly understood. This study investigated these mechanisms using a functional ex vivo bladder cancer tissue slice model combined with n = 64 spatial transcriptomics. Spatial analysis revealed transcriptomic changes involving the immunomodulating gene SPP1 that has been also recently presented as a putative predictive biomarker for neoadjuvant chemotherapy in bladder cancer. Moreover, Non‐Responders exhibited upregulation of chemokines including CXCL1 and CXCL8 and enrichment of immunoregulatory M2 macrophages in tumor regions, suggesting active macrophage recruitment from the stroma. On the contrary, Responders showed upregulation of complement components, proinflammatory macrophage subsets and signals associated with cytotoxic lymphocyte recruitment. Tissue slices corresponding cell cultures confirmed overexpression of immunomodulating markers including checkpoints PD‐L1 and PD‐L2 in Non‐Responder cancer cells upon Gem/Cis treatment. Using TCGA bladder cancer data, the transcriptomic gene set was further validated revealing a prognostic signature associated with patients' outcome. These findings uncover a novel mechanism of chemotherapy resistance in bladder cancer driven by tumor–stromal interactions and macrophage recruitment and suggest that targeting macrophage infiltration may improve chemotherapy response in bladder cancer. Chemoresistance in bladder cancer: Macrophage recruitment associated with CXCL1, CXCL5 and CXCL8 expression is characteristic of Gemcitabine/Cisplatin (Gem/Cis) Non‐Responder tumors (right side) while Responder tumors did not show substantial tumor‐stromal crosstalk (left side). All biological icons are attributed to Bioicons: carcinoma, cancerous‐cell‐1,2,3,4,5, (apoptotic adaptation) fibroblast‐1,2,3,4,5, dendritic‐cell‐2, macrophage, nk‐cell icon by Servier https://smart.servier.com/ is licensed under CC‐BY 3.0 Unported https://creativecommons.org/licenses/by/3.0/.

Aims Different regions of oral squamous cell carcinoma (OSCC) have particular histopathological characteristics, and the individual histological characteristics of the tumors are poorly understood. Therefore, calculating the proportion of tumor cells in different regions that allow assessment of the prognostic outcomes for OSCC patients would be of great clinical significance. Methods and Results We established an open‐source software‐based analytic pipeline that defines the inner tumor and invasive tumor front (ITF) in pancytokeratin‐stained whole slide images (WSIs) and quantifies the tumor‐stroma ratio (TSR) within the two regions. We applied this method to 114 patients with OSCC and predicted patient prognosis by the TSR. The proportion of tumor area in the inner tumor was generally higher than that in the ITF (p < 0.0001). TSR was an independent prognostic factor for overall survival (OS) (p = 0.016), disease‐free survival (DFS) (p = 0.026), and relapse‐free survival (RFS) (p = 0.037) in inner tumor, and TSR was an independent prognostic factor for OS (p = 0.00052), DFS (p = 0.035), and metastasis‐free survival (MFS) (p = 0.038) in the ITF. Tumor‐low status was associated with poorer prognosis. There was a significant correlation between the TSR and perineural invasion (PNI) in the inner tumor (p = 0.009). Conclusions The histopathological characteristics of different regions of OSCC may be used to develop the potential prognostic markers. The TSR of the inner tumor is more targeted in predicting prognosis and accurately assesses the risk of PNI+. Different regions of oral squamous cell carcinoma (OSCC) have particular histopathological and molecular characteristics. Histopathological‐based models may be used to stratify patients into low‐ and high‐risk classes. TSRs of the inner tumor and invasive tumor front can predict the prognosis of OSCC patients.

Collagen, the main component of the tumor microenvironment, plays a key role in the development of breast cancer (BCa); however, the specific changes in its spatial organization during tumor progression have not been definitively elucidated. The existing and available methods for assessing the morphometric parameters of the stroma's fibrous component are insufficient for a detailed description of the state of collagen fibers and for assessing its changes to evaluate the aggressiveness of the BCa course. The aim of the work was to develop an algorithm for microphoto analysis to assess the spatial organization of collagen in BCa tissue of patients with different clinical statuses. The study was conducted on 60 tissue samples of stage I‐II BCa. The processed images were analyzed using the software packages CurveAlign v4.0 and imagej. We established that the increase in BCa stage and the decrease in tumor differentiation grade are associated with decreased length, width, and straightness of collagen fibers, as well as their increased density. The formation of an aggressive basal molecular BCa subtype was accompanied by an increase in tumor‐stroma ratio. The obtained results indicate the possibility of practical application of the developed algorithm for evaluating the spatial organization of collagen in BCa tissue to predict the aggressiveness of the disease course. In order to assess the condition of the tumor collagen matrix, we developed an algorithm for microphoto analysis, which uses Malory's trichrome staining, and also involves specialized software packages (curve align and imagej) for morphometric studies. After completing the analysis, we obtained morphometric indicators of the mammary gland malignant neoplasms stromal fibrous components.

The hallmarks of cancer extend beyond genetic anomalies to encompass a sophisticated tumor microenvironment, involving interactions between cancer and non‐cancer cells within a dynamic biophysical setting, influencing cancer progression. The tumor microenvironment is multifaceted, and it is increasingly clear that the interaction and interdependence of these different facets need to be better understood. Tissue engineering of 3D in vitro models of the tumor microenvironment provides an opportunity to study these interactions and their interdependence on cancer progression. Cancer metastasis still poses a major challenge, accounting for 90% of cancer‐related deaths. This accentuates the critical need to establish patient‐specific model systems that replicate tumor complexity at all stages of progression. Herein, we outline the latest advancements of in vitro 3D models of the tumor microenvironment and the different tools utilized to analyze such models. Henceforth, the interaction of the multifaceted tumor microenvironment can be elucidated using such sophisticated in vitro tools. The tumor microenvironment is a dynamic, multifaceted complex system of interdependent cellular, biochemical, and biophysical components. Three‐dimensional in vitro models of the tumor microenvironment enable a better understanding of these interactions and their impact on cancer progression and therapeutic resistance.

Background Research on the impact of tumor-infiltrating immune cells(TIICs) combined with systemic inflammatory response (SIR) factors on cervical lesions and the prognosis of squamous cell cervical cancer (SCC) is limited. Therefore, this study aimed to evaluate the predictive and prognostic significance of TIICs and SIR factors in cervical epithelial lesions, specifically non-cervical epithelial lesions (NC), high-grade squamous intraepithelial lesions (HSIL), and SCC. Methods This retrospective study analyzed 163 patients in three cohorts: NC ( n  = 59), HSIL ( n  = 52), and SCC ( n  = 52). Tumor-infiltrating immune cells (TIICs) in the tumor/lesion center and adjacent stroma were assessed via immunohistochemistry and multiplex immunofluorescence, while systemic inflammatory response (SIR) factors were derived from preoperative blood counts. The primary outcome was relapse-free survival (RFS) in the SCC cohort, analyzed using Cox proportional hazards regression. Results TIICs were significantly elevated in the HSIL group compared with those in the NC group, accompanied by reduced platelet counts (PLT). The tumor stroma (TS) exhibited a greater degree of TIICs than the tumor/lesion center (TC) in both the HSIL and SCC groups. The presence of CD163+, CD11b+, and FOXP3 + TIICs, along with PLT levels, emerged as key indicators associated with the advanced histological stage. Compared to tTIICs, sTIICs demonstrated superior diagnostic performance in differentiating between HSIL and SCC groups. Lower levels of PLT (hazard ratio [HR] = 5.047, 95% confidence interval [CI]:1.373–18.540, P  = 0.015), higher CD4 + T cells (HR = 0.211, 95%CI:0.062–0.722, P  = 0.008), and FOXP3 + regulatory T cells (Tregs) (HR = 0.245, 95%CI:0.073–0.820, P  = 0.010) were identified as poor prognostic indicators for recurrence-free survival (RFS) in SCC. A combination of FOXP3 + Tregs and PLT provided a more robust prediction of SCC recurrence. An increase in exhausted CD4 + T cells likely explains the observation that higher CD4 + T-cell infiltration correlated with lower RFS in SCC. Conclusion The spatial distribution of TIICs, particularly the density in the tumor stroma, increases across the histological spectrum of cervical lesion severity. A signature combining FOXP3 + Treg cells and preoperative platelet counts provides a robust model for predicting SCC recurrence. Furthermore, the accumulation of exhausted CD4 + T cells appears to be a hallmark of disease advancement and poor prognosis, offering potential targets for personalized immunotherapy.

Colorectal cancer (CRC) with peritoneal dissemination remains a major therapeutic challenge because of poor prognosis and limited treatment options. Experimental models that accurately recapitulate tumor–mesothelial interactions are scarce. Here, we report the establishment of a novel autologous paired model comprising a CRC cell line (OMUCR‐1) and matched cancer‐associated mesothelial cells (CAmeso), both simultaneously derived from the malignant ascites of the same patient. Lineage marker analysis using qPCR demonstrated that OMUCR‐1 selectively expressed epithelial markers ( EPCAM, KRT20 ), whereas CAmeso strongly expressed mesothelial‐mesenchymal markers (ACTA2, MSLN) and lacked epithelial marker expression. These mutually exclusive expression patterns confirm that the two cell populations are phenotypically distinct and rule out cross‐contamination. OMUCR‐1 displayed strong tumorigenic capacity across multiple transplantation models. CAmeso enhanced CRC cell migration and invasion in vitro, and co‐transplantation with OMUCR‐1 resulted in larger tumors enriched with αSMA‐positive stromal components. RNA sequencing of co‐injected xenografts revealed increased expression of murine stromal Fgfr3. Treatment with the FGFR inhibitor BGJ398 reduced tumor growth and decreased stromal FGFR3‐positive components, suggesting that stromal FGFR3 may represent a potential microenvironmental vulnerability in CRC with peritoneal dissemination. This autologous CRC‐mesothelial system provides a physiologically relevant platform for dissecting tumor‐stroma interactions in peritoneal metastasis and may advance stromal‐targeted therapeutic strategies.