The tumor-stroma ratio in giant cell tumor of bone: associations with the immune microenvironment and responsiveness to denosumab treatment.

BACKGROUND: Currently, there is limited understanding regarding the clinical significance of the tumor-stroma ratio (TSR) in giant cell tumor of bone (GCTB). Hence, we aimed to investigate the distribution of TSR in GCTB and explore its correlation with various clinicopathologic factors, immune microenvironment, survival prognosis, and denosumab treatment responsiveness. METHODS: We conducted a multicenter cohort study comprising 426 GCTB patients treated at four centers. TSR was evaluated on hematoxylin and eosin-stained and immunofluorescent sections of tumor specimens. Immunohistochemistry was performed to assess CD3+, CD4+, CD8+, CD20+, PD-1+, PD-L1+, and FoxP3+ TIL subtypes as well as Ki-67 expression levels in 426 tissue specimens. These parameters were then analyzed for their correlations with patient outcomes [local recurrence-free survival (LRFS) and overall survival (OS)], clinicopathological features, and denosumab treatment responsiveness. RESULTS: Low TSR was significantly associated with poor LRFS and OS in both cohorts. Furthermore, TSR was also correlated with multiple clinicopathological features, TIL subtype expression, and denosumab treatment responsiveness. TSR demonstrated similar predictive capabilities as the conventional Campanacci staging system for predicting patients' LRFS and OS. CONCLUSION: The results of this study provide evidence supporting the use of TSR as a reliable prognostic tool in GCTB and as a predictor of denosumab treatment responsiveness. These findings may aid in developing individualized treatment strategies for GCTB patients in the future.

Prognostic value of tumor-stroma ratio in clear cell renal cell carcinoma after surgery.

Background: Clear cell renal cell carcinoma (ccRCC) is one of the most common urological tumors, and its incidence is increasing year by year. Tumor stroma ratio (TSR) can reflect the amount of stromal component around tumor cells, and can independently predict the prognosis of tumor. This study aims to evaluate the prognostic value of TSR in ccRCC patients. Methods: From January 2010 to December 2015, clinical and histopathological data of patients with ccRCC patients who underwent surgical operation were collected. Using TSR (50%) as the cut-off value, the patients were divided into low-TSR group (<50%) and high-TSR group (≥50%). The clinicopathological characteristics and survival status of patients were compared between the two groups. Univariate and multivariate analyses were used to identify the prognostic factors for overall survival (OS), cancer-specific survival (CSS), metastasis-free survival (MFS). Results: The mean age of 569 patients was 56.84±12.76 years old. There were 401 males and 168 females. According to the TSR, patients were divided into low-TSR group (n=333, 58.5%) and high-TSR group (n=236, 41.5%). The median follow-up time was 67.0 months (interquartile range, 33.0-72.0 months). The 5-year OS, CSS and MFS were 91.2%, 94.6% and 91.0%, respectively. The 5-year OS, CSS and MFS were 84.2%,89.7% and 82.7% in the high-TSR group and 96.1%, 98.0% and 96.0% in the low-TSR group (P<0.05). Multivariate analysis showed that age >60 years [hazard ratio (HR) =2.455, 95% confidence interval (CI): 1.292-4.668, P=0.006), tumor grade (HR =6.580, 95% CI: 3.276-13.216, P<0.001) and TSR (HR =2.611, 95% CI: 1.265-5.387, P=0.009) were independent prognostic factors for OS. Multivariate analysis showed that tumor stage (HR =3.213, 95% CI: 1.437-7.184, P=0.004), tumor grade (HR =6.102, 95% CI: 2.664-13.976, P<0.001) and TSR (HR =2.653, 95% CI: 1.063-6.621, P=0.03) were independent prognostic factors for CSS. Multivariate analysis showed that tumor stage (HR =4.805, 95% CI: 2.677-8.624, P<0.001), tumor grade (HR =6.423, 95% CI: 3.432-12.020, P<0.001), hemorrhage (HR =0.514, 95% CI: 0.265-0.996, P=0.049) and TSR (HR =2.370, 95% CI: 1.264-4.443, P=0.007) were independent prognostic factors for MFS. Conclusions: TSR is a new independent prognostic risk factor for ccRCC patients. The assessment of TSR is simple and cost-effective, and it is a useful supplement added to the pathological evaluation system.

Tumor microenvironment characteristics association with clinical outcome in patients with resected intestinal-type gastric cancer.

BACKGROUND: Tumor microenvironment (TME) characteristics including tumor stroma ratio (TSR), tumor budding (TB), and tumor-infiltrating lymphocytes (TILs) were examined in resected gastric cancer. These TME features have been shown to indicate metastatic potential in colon cancer, and intestinal-type gastric cancer (IGC) has pathological similarities with that malignancy. METHODS: TSR, TB, and TILs were quantified in routine histological sections from 493 patients with IGC who underwent radical resection at 2 university hospitals in China from 2010 to 2016. TME variables were dichotomized as follows: TSR (50%), TILs (median), TB per international guidelines (4 buds/0.785mm2), and platelet-lymphocyte ratio (PLR) per survival ROC. Association of TME features with patient clinicopathological characteristics, time-to-recurrence (TTR), and cancer-specific-survival (CSS) were examined using univariate and multivariate analysis, including a relative contribution analysis by Cox regression. RESULTS: Patients whose tumors showed high TSR or high TB or low TILs were each significantly associated with increased T and N stage, higher histological grade, and poorer TTR and CSS at 5 years. Only TSR and N stage were independently associated with TTR and CSS after adjustment for covariates. PLR was only independently associated with TTR after adjustment for covariates. Among the variables examined, only TSR was significantly associated with both TTR (HR 1.72, 95% CI, 1.14-2.60, P = .01) and CSS (HR 1.62, 95% CI, 1.05-2.51, P = .03) multivariately. Relative contribution to TTR revealed that the top 3 contributors were N stage (45.1%), TSR (22.5%), and PLR (12.9%), while the top 3 contributors to CSS were N stage (59.9%), TSR (14.7%), and PLR (10.9%). CONCLUSIONS: Among the examined TME features, TSR was the most robust for prognostication and was significantly associated with both TTR and CSS. Furthermore, the relative contribution of TSR to patient TTR and CSS was second only to nodal status.

Results from the UNITED study: a multicenter study validating the prognostic effect of the tumor-stroma ratio in colon cancer.

BACKGROUND: The TNM (tumor-node-metastasis) Evaluation Committee of Union for International Cancer Control (UICC) and College of American Pathologists (CAP) recommended to prospectively validate the cost-effective and robust tumor-stroma ratio (TSR) as an independent prognostic parameter, since high intratumor stromal percentages have previously predicted poor patient-related outcomes. PATIENTS AND METHODS: The 'Uniform Noting for International application of Tumor-stroma ratio as Easy Diagnostic tool' (UNITED) study enrolled patients in 27 participating centers in 12 countries worldwide. The TSR, categorized as stroma-high (>50%) or stroma-low (≤50%), was scored through standardized microscopic assessment by certified pathologists, and effect on disease-free survival (DFS) was evaluated with 3-year median follow-up. Secondary endpoints were benefit assessment of adjuvant chemotherapy (ACT) and overall survival (OS). RESULTS: A total of 1537 patients were included, with 1388 eligible stage II/III patients curatively operated between 2015 and 2021. DFS was significantly shorter in stroma-high (n = 428) than in stroma-low patients (n = 960) (3-year rates 70% versus 83%; P < 0.001). In multivariate analysis, TSR remained an independent prognosticator for DFS (P < 0.001, hazard ratio 1.49, 95% confidence interval 1.17-1.90). As secondary outcome, DFS was also worse in stage II and III stroma-high patients despite adjuvant treatment (3-year rates stage II 73% versus 92% and stage III 66% versus 80%; P = 0.008 and P = 0.011, respectively). In stage II patients not receiving ACT (n = 322), the TSR outperformed the American Society of Clinical Oncology (ASCO) criteria in identifying patients at risk of events (event rate 21% versus 9%), with a higher discriminatory 3-year DFS rate (stroma-high 80% versus ASCO high risk 91%). A trend toward worse 5-year OS in stroma-high was noticeable (74% versus 83% stroma-low; P = 0.102). CONCLUSION: The multicenter UNITED study unequivocally validates the TSR as an independent prognosticator, confirming worse outcomes in stroma-high patients. The TSR improved current selection criteria for patients at risk of events, and stroma-high patients potentially experienced chemotherapy resistance. TSR implementation in pathology diagnostics and international guidelines is highly recommended as aid in personalized treatment.

Microenvironment, systemic inflammatory response and tumor markers considering consensus molecular subtypes of colorectal cancer.

Introduction: Colorectal carcinomas (CRC) are one of the most frequent malignancies worldwide. Based on gene expression profile analysis, CRCs can be classified into four distinct subtypes also known as the consensus molecular subtypes (CMS), which predict biological behaviour. Besides CMS, several other aspects of tumor microenvironment (TME) and systemic inflammatory response (SIR) influence the outcome of CRC patients. TME and inflammation have important role in the immune (CMS1) and mesenchymal (CMS4) subtypes, however, the relationship between these and systemic inflammation has not been assessed yet. Our objective was to evaluate the connection between CMS, TME and SIR, and to analyze the correlation between these markers and routinely used tumor markers, such as CEA (Carcinoembryonic Antigen) and CA19-9 (Carbohydrate Antigen 19-9). Methods: FFPE (Formalin Fixed Paraffin Embedded) samples of 185 CRC patients were collected. TME was described using tumor-stroma ratio (TSR), Klintrup-Makinen (KM) grade, and Glasgow Microenvironment Score (GMS). CMS classification was performed on tissue microarray using MLH1, PMS2, MSH2 and MSH6, and pan-cytokeratin, CDX2, FRMD6, HTR2B and ZEB1 immunohistochemical stains. Pre-operative tumor marker levels and inflammatory markers [C-reactive protein - CRP, albumin, absolute neutrophil count (ANC), absolute lymphocyte count (ALC), absolute platelet count (APC)] and patient history were retrieved using MedSolution database. Results: Amongst TME-markers, TSR correlated most consistently with adverse clinicopathological features (p < 0.001) and overall survival (p < 0.001). Elevated CRP and modified Glasgow Prognostic Score (mGPS) were associated with worse outcome and aggressive phenotype, similarly to tumor markers CEA and CA19-9. Stroma-Tumor Marker score (STM score), a new combined score of CA19-9 and TSR delivered the second best prognostication after mGPS. Furthermore, CMS4 showed association with TSR and several laboratory markers (albumin and platelet derived factors), but not with other SIR descriptors. CMS did not show any association with CEA and CA19-9 tumor markers. Conclusion: More routinely available TME, SIR and tumor markers alone and in combination deliver reliable prognostic data for choosing the patients with higher risk for propagation. CMS4 is linked with high TSR and poor prognosis, but in overall, CMS-classification showed only limited effect on SIR- and tumor-markers.

Tumor-stroma ratio in preoperative biopsies and matched surgical specimens in oral squamous cell carcinoma: Concordance and impact on recurrence-free and overall survival.

Stroma-richness is commonly associated with decreased survival times as well as advanced tumor stages in various malignant tumors. A previous study on laryngeal squamous cell carcinomas showed very good agreement for tumor-stroma ratio assessment between pre-treatment biopsies and resection specimens. We therefore aimed to determine whether similar results could be shown for oral squamous cell carcinomas. 107 preoperative biopsies and matched surgical specimens were obtained from the histological archive, dating from 2011-2022. Tumor-stroma ratio was determined on all samples and cases were divided into stroma-rich (≥50% stroma) and stroma-poor (<50% stroma). Results were then correlated with recurrence-free and overall survival. Tumor-stroma ratio showed substantial agreement between preoperative biopsies and surgical specimens with a kappa correlation coefficient of 0.643. Concerning preoperative biopsies, 28 cases were stroma-rich (26.2%), in the group of tumor resections, 32 cases were stroma-rich (29.9%). No association with either recurrence-free or overall survival could be shown for both groups (p-values 0.158-0.495). Concordance between pre-treatment biopsies and resections was substantial in our study, however, as no association with survival times could be demonstrated, the prognostic significance in our cohort remains unclear. This might be attributable to the fact that almost 75% of our patients presented with early-stage tumors, which sometimes seem to show a less pronounced prognostic effect of the tumor-stroma ratio.

Development of an algorithm for biomedical image analysis of the spatial organization of collagen in breast cancer tissue of patients with different clinical status.

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.

Tumor stroma ratio, tumor stroma maturity, tumor-infiltrating immune cells in relation to prognosis, and neoadjuvant therapy response in esophagogastric junction adenocarcinoma.

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.

Comparison of Clinico-Demographic and Histological Parameters Between Young and Old Patients With Oral Squamous Cell Carcinoma.

INTRODUCTION: Among the epithelial malignancies of the head and neck region, oral squamous cell carcinoma (OSCC) arising from the oral mucosa is the commonest type. OSCC is common in the older population; however, recent epidemiological data indicate an increase in the incidence in the younger age group. The present study was designed to compare the clinicopathological characteristics of OSCC between young and old South Indian patients. METHODS: All the histopathologically confirmed cases of OSCC were retrieved from the department archives. Patients aged more than 40 years were considered Group I, and patients aged less than or equal to 40 were considered Group II. Age, gender, laterality, site, degree of keratinization, nuclear pleomorphism, pattern of invasion, lymphoplasmacytic infiltration, grade, tumor budding (TB), and tumor stroma ratio (TSR) were assessed. RESULTS: Among 510 patients reported with OSCC, 442 were aged above 40 years, and 68 were aged 40 years or younger. Nuclear pleomorphism, TB, and stroma-rich ratio were statistically higher in younger OSCC patients (p=0.00). CONCLUSION: The results of our study support the fact that OSCC in younger individuals is more aggressive. Targeting TB and tumor stroma could provide new strategies for the management of OSCC.

Feasibility and effectiveness of automatic deep learning network and radiomics models for differentiating tumor stroma ratio in pancreatic ductal adenocarcinoma.

OBJECTIVE: This study aims to compare the feasibility and effectiveness of automatic deep learning network and radiomics models in differentiating low tumor stroma ratio (TSR) from high TSR in pancreatic ductal adenocarcinoma (PDAC). METHODS: A retrospective analysis was conducted on a total of 207 PDAC patients from three centers (training cohort: n = 160; test cohort: n = 47). TSR was assessed on hematoxylin and eosin-stained specimens by experienced pathologists and divided as low TSR and high TSR. Deep learning and radiomics models were developed including ShuffulNetV2, Xception, MobileNetV3, ResNet18, support vector machine (SVM), k-nearest neighbor (KNN), random forest (RF), and logistic regression (LR). Additionally, the clinical models were constructed through univariate and multivariate logistic regression. Kaplan-Meier survival analysis and log-rank tests were conducted to compare the overall survival time between different TSR groups. RESULTS: To differentiate low TSR from high TSR, the deep learning models based on ShuffulNetV2, Xception, MobileNetV3, and ResNet18 achieved AUCs of 0.846, 0.924, 0.930, and 0.941, respectively, outperforming the radiomics models based on SVM, KNN, RF, and LR with AUCs of 0.739, 0.717, 0.763, and 0.756, respectively. Resnet 18 achieved the best predictive performance. The clinical model based on T stage alone performed worse than deep learning models and radiomics models. The survival analysis based on 142 of the 207 patients demonstrated that patients with low TSR had longer overall survival. CONCLUSIONS: Deep learning models demonstrate feasibility and superiority over radiomics in differentiating TSR in PDAC. The tumor stroma ratio in the PDAC microenvironment plays a significant role in determining prognosis. CRITICAL RELEVANCE STATEMENT: The objective was to compare the feasibility and effectiveness of automatic deep learning networks and radiomics models in identifying the tumor-stroma ratio in pancreatic ductal adenocarcinoma. Our findings demonstrate deep learning models exhibited superior performance compared to traditional radiomics models. KEY POINTS: • Deep learning demonstrates better performance than radiomics in differentiating tumor-stroma ratio in pancreatic ductal adenocarcinoma. • The tumor-stroma ratio in the pancreatic ductal adenocarcinoma microenvironment plays a protective role in prognosis. • Preoperative prediction of tumor-stroma ratio contributes to clinical decision-making and guiding precise medicine.

Tumor-Infiltrating Lymphocytes and Tumor-Stroma Ratio on Early-Stage Cervix Carcinoma: Prognostic Value of Two Distinct Morphological Patterns of Microenvironment.

Background Tumor progression is influenced by the complex network of different cellular elements that make up its microenvironment. Tumor-infiltrating lymphocytes (TILs) and stroma characteristics reflect two faces of the intricate mechanisms involved in the tumor-host interaction and can be easily evaluated by routine histological examination. Their prognostic value could be demonstrated in different tumor tumor types, but they are poorly explored in cervical cancer. Methodology In this retrospective study, we analyzed the association of TILs, tumor-stroma ratio (TSR), and pattern of stromal fibroblasts with prognosis and classical clinicopathological variables. We studied 61 patients with early-stage cervical cancer. We reviewed histological type, tumor grade, Silva pattern of invasion for adenocarcinomas, tumor thickness, depth of stromal invasion, lymph vascular space invasion, and lymph node status. The median follow-up was 37.77 months (range 4.77 to 112.37 months). Results The TSR did not correlate with any clinicopathological features or disease-free and overall survival. On the other hand, the reactive pattern of stroma composed of larger fibroblasts and less collagenization was associated with the FIGO IB2 stage (p=0.04), larger tumor (p=0.03), and deeper infiltration (p=0.005). There were more recurrences in the group of reactive stroma (33.13% vs. 11.5%), although the difference did not reach statistical significance. Reactive stroma was associated with lower survival free of recurrence (p=0.05) and overall survival (p=0.009). High TILs were associated with squamous cell type (p=0.003), higher tumor grade (p=0.02), and more LVSI (p=0.02). Tumors with higher TILs presented higher free recurrence interval (p=0.06) and overall survival (p=0.03). No association was observed between stroma characteristics and TILs. Conclusions Our study suggested that although immune activation and stromal changes are important features of microenvironment remodeling during tumoral progression, they are independent, following distinct carcinogenetic pathways. Pathological assessment of stroma characteristics and TILs adds significant prognostic information and demonstrates how a simple routine laboratory assessment can generate a better understanding of biological phenomena.

Combining the tumor-stroma ratio with tumor-infiltrating lymphocytes improves the prediction of pathological complete response in breast cancer patients.

PURPOSE: The tumor-stroma ratio (TSR) is a common histological parameter that measures stromal abundance and is prognostic in breast cancer (BC). However, more evidence is needed on the predictive value of the TSR for the pathological complete response (pCR) to neoadjuvant chemotherapy (NAC). The purpose of this study was to determine the importance of the TSR in predicting pCR in NAC settings. METHOD: We evaluated the TSR on pretreatment biopsies of 912 BC patients from four independent Chinese hospitals and investigated the potential value of the TSR for predicting pCR. Meanwhile, stromal tumor-infiltrating lymphocytes (sTILs) were assessed, and we evaluated the predictive value of the combination of sTILs and TSR (TSRILs). RESULTS: Patients with low stroma showed a higher pCR rate than those with high stroma among the four independent hospitals, and in multivariate analysis, the TSR was proven to be an independent predictor for pCR to NAC with an odds ratio of 1.945 (95% CI 1.230-3.075, P = 0.004). Moreover, we found that TSRILs could improve the area under the curve (AUC) for predicting pCR from 0.750 to 0.785 (P = 0.039); especially in HER2-negative BCs, the inclusion of TSRILs increased the AUC from 0.801 to 0.835 in the discovery dataset (P = 0.048) and 0.734 to 0.801 in the validation dataset (P = 0.003). CONCLUSION: TSR and sTILs can be easily measured in pathological routines and provide predictive information without additional cost; with more evidence from clinical trials, TSRILs could be a candidate to better stratify patients in NAC settings.

Assessment of the Tumor-Stroma Ratio and Tumor-Infiltrating Lymphocytes in Colorectal Cancer: Inter-Observer Agreement Evaluation.

BACKGROUND: To implement the new marker in clinical practice, reliability assessment, validation, and standardization of utilization must be applied. This study evaluated the reliability of tumor-infiltrating lymphocytes (TILs) and tumor-stroma ratio (TSR) assessment through conventional microscopy by comparing observers' estimations. METHODS: Intratumoral and tumor-front stromal TILs, and TSR, were assessed by three pathologists using 86 CRC HE slides. TSR and TILs were categorized using one and four different proposed cutoff systems, respectively, and agreement was assessed using the intraclass coefficient (ICC) and Cohen's kappa statistics. Pairwise evaluation of agreement was performed using the Fleiss kappa statistic and the concordance rate and it was visualized by Bland-Altman plots. To investigate the association between biomarkers and patient data, Pearson's correlation analysis was applied. RESULTS: For the evaluation of intratumoral stromal TILs, ICC of 0.505 (95% CI: 0.35-0.64) was obtained, kappa values were in the range of 0.21 to 0.38, and concordance rates in the range of 0.61 to 0.72. For the evaluation of tumor-front TILs, ICC was 0.52 (95% CI: 0.32-0.67), the overall kappa value ranged from 0.24 to 0.30, and the concordance rate ranged from 0.66 to 0.72. For estimating the TSR, the ICC was 0.48 (95% CI: 0.35-0.60), the kappa value was 0.49 and the concordance rate was 0.76. We observed a significant correlation between tumor grade and the median of TSR (0.29 (95% CI: 0.032-0.51), p-value = 0.03). CONCLUSIONS: The agreement between pathologists in estimating these markers corresponds to poor-to-moderate agreement; implementing immune scores in daily practice requires more concentration in inter-observer agreements.

Significance of Tumor-Stroma Ratio (TSR) in Predicting Outcomes of Malignant Tumors.

Background and Objectives: The present study aimed to elucidate the distribution and the prognostic implications of tumor-stroma ratio (TSR) in various malignant tumors through a meta-analysis. Materials and Methods: This meta-analysis included 51 eligible studies with information for overall survival (OS) or disease-free survival (DFS), according to TSR. In addition, subgroup analysis was performed based on criteria for high TSR. Results: The estimated rate of high TSR was 0.605 (95% confidence interval (CI) 0.565-0.644) in overall malignant tumors. The rates of high TSR ranged from 0.276 to 0.865. The highest rate of high TSR was found in endometrial cancer (0.865, 95% CI 0.827-0.895). The estimated high TSR rates of colorectal, esophageal, and stomach cancers were 0.622, 0.529, and 0.448, respectively. In overall cases, patients with high TSR had better OS and DFS than those with low TSR (hazard ratio (HR) 0.631, 95% CI 0.542-0.734, and HR 0.564, 95% CI 0.0.476-0.669, respectively). Significant correlations with OS were found in the breast, cervical, colorectal, esophagus, head and neck, ovary, stomach, and urinary tract cancers. In addition, there were significant correlations of DFS in breast, cervical, colorectal, esophageal, larynx, lung, and stomach cancers. In endometrial cancers, high TSR was significantly correlated with worse OS and DFS. Conclusions: The rate of high TSR was different in various malignant tumors. TSR can be useful for predicting prognosis through a routine microscopic examination of malignant tumors.

The tumor-stroma ratio and the immune microenvironment improve the prognostic prediction of pancreatic ductal adenocarcinoma.

Tumor-infiltrating immune cells and fibroblasts are significant components of the tumor microenvironment (TME) of pancreatic ductal adenocarcinoma (PDAC), and they participate in tumor progression as closely as tumor cells. However, the relationship between the features of the TME and patient outcomes and the interactions among TME components are still unclear. In this study, we evaluated the PDAC TME in terms of the quantity and location of cluster of differentiation (CD)4+ T cells, CD8+ T cells, macrophages, stromal maturity, and tumor-stroma ratio (TSR), as evaluated by immunohistochemical staining of serial whole-tissue sections from 116 patients with PDAC. The density of T cells and macrophages (mainly activated macrophages) was significantly higher at the invasive margins (IMs) than at the tumor center (TC). CD4+ T cells were significantly association with all the other tumor-associated immune cells (TAIs) including CD8, CD68 and CD206 positive cells. Tumors of the non-mature (intermediate and immature) stroma type harbored significantly more CD8+ T cells at the IMs and more CD68+ macrophages at the IMs and the TC. The density of CD4+, CD8+, and CD206+ cells at the TC; CD206+ cells at the IMs; and tumor-node-metastasis (TNM) staging were independent risk factors for patient outcomes, and the c-index of the risk nomogram for predicting the survival probability based on the TME features and TNM staging was 0.772 (95% confidence interval: 0.713-0.832). PDAC harbored a significantly immunosuppressive TME, of which the IMs were the hot zones for TAIs, while cells at the TC were more predictive of prognosis. Our results indicated that the model based on the features of the TME and TNM staging could predict patient outcomes.

Tumor-Stroma Ratio in Colorectal Cancer-Comparison between Human Estimation and Automated Assessment.

The tumor-stroma ratio (TSR) has been repeatedly shown to be a prognostic factor for survival prediction of different cancer types. However, an objective and reliable determination of the tumor-stroma ratio remains challenging. We present an easily adaptable deep learning model for accurately segmenting tumor regions in hematoxylin and eosin (H&E)-stained whole slide images (WSIs) of colon cancer patients into five distinct classes (tumor, stroma, necrosis, mucus, and background). The tumor-stroma ratio can be determined in the presence of necrotic or mucinous areas. We employ a few-shot model, eventually aiming for the easy adaptability of our approach to related segmentation tasks or other primaries, and compare the results to a well-established state-of-the art approach (U-Net). Both models achieve similar results with an overall accuracy of 86.5% and 86.7%, respectively, indicating that the adaptability does not lead to a significant decrease in accuracy. Moreover, we comprehensively compare with TSR estimates of human observers and examine in detail discrepancies and inter-rater reliability. Adding a second survey for segmentation quality on top of a first survey for TSR estimation, we found that TSR estimations of human observers are not as reliable a ground truth as previously thought.

Tumor-Stroma Ratio in ER+/HER2- Breast Cancer: Is it a Tool for Treatment Decision?

PURPOSE: The primary aim of this study is to determine the relationship between tumor-stroma ratio (TSR) and traditional prognostic factors in luminal early breast cancer in women treated at the medical oncology department of the military hospital of Rabat in Morocco. METHODS: A retrospective study was performed on primary invasive ER+/HER2- breast cancer in the period from January 1st, 2019 to December 31st, 2019. Prognostic factors included age, tumour size, lymph nodes status, Scarff-Bloom-Richardson grading, lymphovascular invasion (LVI), Ki67 and the stage of the disease. The type of Adjuvant systemic therapy was also reported .Two independent pathologists have assessed TSR by microscopic evaluation of haematoxylin and eosin tumor slides .Patients with less than 50% stroma were classified as low-stroma, the others are classified as high-stroma. RESULTS: Of 53 ER+/HER2- operable breast cancer, 41.5% patients had low-stroma and 58.5% patients had high stroma-tumour. High stroma was significantly associated with more stage III (p=0.041), more LVI (0.034), high Ki-67 (p=0.002) and more luminal B disease (p=0.001). Also, high stroma received more adjuvant chemotherapy (p=0.005). The results are maintained in univariate analysis. CONCLUSIONS: Data suggest that TSR can be used to guide decisions on adjuvant systemic therapy for ER+/HER2- breast cancer. The integration in routine of this simple and reproducible parameter requires a homogenization of the techniques as well as a prospective validation.

Prognostic evaluation of cancer associated fibrosis and tumor budding in colorectal cancer.

Colorectal carcinoma (CRC) is the second most common cancer and third leading cause of cancer-related deaths worldwide. Although the staging system provides a standardized guidance in treatment regimens, the clinical outcome in patients with colon cancer at the same TNM stage may vary dramatically. Thus, for better predictive accuracy, further prognostic and/or predictive markers are required. Patients who underwent curative surgery for colorectal cancer in past 3 years at a tertiary care hospital were retrospectively included in this cohort study to evaluate the prognostic indicators, tumor-stroma ratio (TSR) and tumor budding (TB) on histopathological sections and correlated them with pTNM staging, histopathological grading, tumor size, and lymphovascular and perineural invasion in patients with colo-rectal cancer. TB was strongly associated with advanced stage of the disease along with lympho-vascular and peri-neural invasion and it can be used as an independent adverse prognostic factor. TSR showed a better sensitivity, specificity, PPV and NPV as compared to TB in patients having poorly differentiated adenocarcinoma than those with moderately or well differentiated.

Tumor-stroma ratio predicts prognosis and PD-L1 expression in hepatocellular carcinoma.

BACKGROUND: With the in-depth research on the tumor microenvironment, the tumor stroma is considered to play a leading role in malignant tumor behavior, and PD-L1 is also related to the tumor stroma. The tumor-stroma ratio (TSR) has been regarded as a novel prognostic factor in many cancers. Our study aims to assess the TSR and PD-L1 clinical value in hepatocellular carcinoma (HCC) patients. METHODS: Ninety-five patients who were diagnosed with HCC were included in our study. TSR was estimated on HCC specimen hematoxylin-eosin staining (HE) sections, and the optimal TSR cut-off value was determined by receiver operating characteristic (ROC) curves. The correlation between the TSR and clinicopathologic features was also calculated. Immunohistochemistry (IHC) staining was also carried out to analyze the PD-L1 expression level in HCCs. RESULTS: The optimal TSR cut-off value was 0.525. The median OS of the stroma-high and stroma-low groups was 27 and 36 months, respectively. The median RFS of the stroma-high and stroma-low groups was 14.5 and 27 months, respectively. In the Cox multivariate analysis, the TSR was an independent prognostic factor for HCC overall survival (OS) and recurrence-free survival (RFS) in patients who underwent liver resection. IHC staining revealed TSR-high HCC samples with high PD-L1-positive cell expression. CONCLUSIONS: Our results suggest that the TSR can predict the prognosis of HCC patients who underwent liver resection. The TSR is related to PD-L1 expression and may be a therapeutic target that can dramatically improve HCC patients' clinical outcomes.

Multiperspective quantitative tumor-stroma ratio reveals histological areas associated with poor outcomes in oral squamous cell carcinoma.

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+.