Association between tumor-stroma ratio and prognosis in solid tumor patients: a systematic review and meta-analysis

Association of High Tumor-Stroma Ratio with Prostate Cancer Progression: Insights from Clinical and Genomic Data

Background

Tumor stroma ratio (TSR) is a prognostic factor in various cancers, but its role in prostate adenocarcinoma (PRAD) remains unclear. This study investigates TSR's prognostic value in PRAD using clinicopathological data, bulk/single-cell RNA sequencing to explore tumor-stroma interactions and identify therapeutic targets.

Methods

Two PRAD cohorts (The Cancer Genome Atlas cohort, TCGA; Lanzhou University Second Hospital, LUSH) were analyzed for TSR associations with clinicopathological features and biochemical recurrence (BCR). TSR was assessed via digital image analysis and expert pathologist review. Publicly available bulk/single-cell RNA sequencing data were analyzed to identify TSR-associated genes and predict drug targets, pathways, and immunotherapy responses. Quantitative real-time PCR validated mRNA expression. In vitro assays assessed cell proliferation, growth, and migration, while in vivo xenograft assays validated BGN's role in promoting tumorigenesis.

Results

TSR significantly correlated with clinicopathological features (age, Gleason score, stage, seminal vesicle invasion, BCR) in both TCGA (n = 453) and LUSH (n = 320) cohorts. High TSR independently predicted BCR in multivariable Cox regression. High TSR was associated with copy number variations, differentially expressed miRNAs/transcription factors, and metabolic pathways. Predicted anti-cancer drug targets, like Ki8751, showed potential benefit in high-TSR patients. High TSR may correlate with poor immunotherapy response. Notably, downregulation of BGN in cancer-associated fibroblasts (CAFs) significantly suppressed cell proliferation, migration, and invasion in vitro, and in vivo xenograft assays confirmed that BGN downregulation inhibited tumor growth.

Conclusion

This study highlights TSR's prognostic significance in prostate cancer and its association with adverse clinical outcomes and complex tumor-stroma interactions, identifying BGN, a stromal cell-related gene, as a potential therapeutic target for CAFs. However, these findings are limited by the retrospective design, necessitating prospective validation.

Mechanistic insight for T-cell exclusion by cancer-associated fibroblasts in human lung cancer

The tumor stroma consists mainly of extracellular matrix, fibroblasts, immune cells, and vasculature. Its structure and functions are altered during malignancy: tumor cells transform fibroblasts into cancer-associated fibroblasts, which exhibit immunosuppressive activities on which growth and metastasis depend. These include exclusion of immune cells from the tumor nest, cancer progression, and inhibition of T-cell-based immunotherapy. To understand these complex interactions, we measure the density of different cell types in the stroma using immunohistochemistry techniques on tumor samples from lung cancer patients. We incorporate these data into a minimal dynamical system, explore the variety of outcomes, and finally establish a spatio-temporal model that explains the cell distribution. We reproduce that cancer-associated fibroblasts act as a barrier to tumor expansion, but also reduce the efficiency of the immune response. Our conclusion is that the final outcome depends on the parameter values for each patient and leads to either tumor invasion, persistence, or eradication as a result of the interplay between cancer cell growth, T-cell cytotoxicity, and fibroblast activity. However, despite the existence of a wide range of scenarios, distinct trajectories, and patterns allow quantitative predictions that may help in the selection of new therapies and personalized protocols.

Prognostic Role of Tumor-Infiltrating Lymphocytes, Tumor Budding, Tumor Border Configuration, and Tumor Stroma Ratio in Colorectal Carcinoma

Histomorphological features like tumor-infiltrating lymphocytes (TIL), tumor budding (TB), tumor stroma ratio (TSR), and tumor border configuration (TBC) may provide important prognostic information for more accurate stratification and personalized therapeutic approach in colorectal cancer (CRC). The objective of the current study was to investigate the prognostic impact of novel histopathological features (TIL, TB, TBC, TSR) and a new combined risk score (CRS) in primary CRC. This cross-sectional observational study was conducted on hematoxylin and eosin (H&E)-stained slides of 65 primary CRC cases. Stromal TIL was categorized into 3 groups: low (0 to 10%), intermediate (15 to 50%), and high (55 to 100%). Tumor budding was counted in 10 HPFs and graded as follows: 0-4 buds-low TB, 5-9 buds-intermediate TB, and 10 or more buds-high TB. TBC was labeled as either pushing or infiltrative. TSR was scored into two groups as high TSR (low stroma as ≤ 50%) and low TSR (high stroma > 50%). A novel CRS was constructed based on TBC, TB, and TSR: Infiltrating TBC, TB score > 5 (median), and low TSR were categorized as risk items. Final categories were as follows: low-risk tumors with ≤ 1 risk item and high-risk tumors with > 1 risk items. TIL showed a significant correlation with histological tumor type; TB was significantly associated with tumor location, grade, T stage, and perineural invasion, while TBC significantly correlated with tumor location only. TSR showed significant association with tumor location and perineural invasion, while the combined risk score significantly correlated with tumor location and grade. Tumor border configuration, tumor budding, tumor stroma ratio, and the newly formed combined risk score are simple, cost-effective, potential markers in colorectal cancer patients, suggesting that their incorporation in the routine histopathological evaluation could be useful in determining the prognosis of colorectal cancer cases.

Tumor-stroma type and tumor-stroma ratio predict neoadjuvant chemotherapy response in breast cancer

OBJECTIVE

Breast cancer is the most common cancer type among women. One of the most important parameters in the prognosis of patients is the response to neoadjuvant chemotherapy. The most important parameter for neoadjuvant chemotherapy success is appropriate patient selection. We investigated the effect of tumor-stroma type and tumor-stroma ratio on neoadjuvant chemotherapy response, using the Residual Cancer Burden scoring systems.

METHODS

Patients diagnosed with breast carcinoma in core needle biopsy materials between 2010 and 2023 and whose neoadjuvant treatments and surgeries were performed in our institution were scanned from the database. A total of 158 patients who met the study criteria were included in the study.

RESULTS

Tumor-stroma ratio and collagen-dominant tumor-stroma type were associated with neoadjuvant chemotherapy resistance, and tumor-stroma ratio was found to be an independent risk factor in treatment response. The probability of response to neoadjuvant chemotherapy treatment was higher in luminal molecular subtype breast cancer patients with low tumor stroma.

CONCLUSION

An effective risk analysis for neoadjuvant chemotherapy treatment is not always possible with current clinicopathological parameters. Tumor-stroma ratio and tumor-stroma type seem useful in predicting neoadjuvant chemotherapy response as a reproducible practical marker and do not require additional cost and time.

Desmoplastic reaction in the microenvironment of head and neck and other solid tumors: the therapeutic barrier

Head and neck squamous cell carcinoma (HNSCC) remains a challenge due to limited prognostic biomarkers and therapeutic options. The tumor microenvironment (TME), particularly the desmoplastic reaction (DR) characterized by stromal fibrosis, plays a crucial role in cancer progression and resistance to therapy. This review aims to summarize the biological significance of DR in HNSCC initiation, progression, and treatment resistance. Histologically, DR in HNSCC correlates with invasion patterns and clinical outcomes, affecting disease-free and overall survival. The interaction between cancer-associated fibroblasts (CAFs) and TME influences immune responses, including resistance to immunotherapy. Notably, human papillomavirus-driven HNSCC exhibits distinct DR characteristics that further influence the prognosis. DR promotes epithelial-mesenchymal transition and cancer cell invasion through CAF-mediated extracellular matrix remodeling and signaling pathways such as transforming growth factor-beta. DR also affects bone invasion and chemotherapy resistance by modulating stromal responses. Therapeutic strategies targeting DR and stromal components show promise in overcoming therapeutic resistance including resistance to immune checkpoint inhibitors. Understanding the role of DR in HNSCC biology and its impact on treatment response is critical to developing effective therapeutic interventions.

Quantifying the tumour vasculature environment from CD-31 immunohistochemistry images of breast cancer using deep learning based semantic segmentation

BACKGROUND

Tumour vascular density assessed from CD-31 immunohistochemistry (IHC) images has previously been shown to have prognostic value in breast cancer. Current methods to measure vascular density, however, are time-consuming, suffer from high inter-observer variability and are limited in describing the complex tumour vasculature morphometry.

METHODS

We propose a method for automatically measuring a range of vascular parameters from CD-31 IHC images, which together provide a detailed description of the vasculature morphology. We first used a U-Net based convolutional neural network, trained and validated using 36 partially annotated whole slide images from 27 patients, to segment vessel structures and tumour regions from which the measurements are taken. The model also segments the vascular smooth muscle, benign epithelium, adipose tissue, stroma, lymphocyte clusters, nerves and CD-31 positive leukocytes, and we applied it to an additional 21 images from 15 patients. Using these segmentations, we investigated the relationship between the various tissue types and the vasculature and studied the relationship of various vascular parameters with clinical parameters. We also performed a 3D histology analysis on a separate tumour sample as a proof of principle, providing a more comprehensive visualization of vasculature morphology compared to the standard 2D cross-section of a tissue sample.

RESULTS

Using two-way cross-validation, we show that vessels were accurately segmented, with Dice scores of 0.875 and 0.856, and were accurately identified, with F1 scores of 0.777 and 0.748. All vascular parameters exhibit strong ( r > 0.7 ) and significant (p<0.001) correlations with measurements taken from the manual ground truth vessel segmentations. A significant relationship between the major/minor axis ratio, a measure of elongation, and the tumour grade was found.

CONCLUSION

Our proposed method shows promise as a tool for studying the tumour vasculature and its relationship with surrounding cells and tissue types. Furthermore, the correlation with tumour grade highlights the clinical relevance of our approach. These findings suggest that our method could have substantial implications for improving prognostic assessments and personalizing therapeutic strategies in breast cancer treatment.

Tumor Budding, Poorly Differentiated Clusters, and Stroma Percentage in Uterine Endometrioid Carcinomas Are Morphologic Findings Associated With Adverse Clinical Outcomes

Uterine endometrioid carcinoma (UEC) has well-defined morphologic features that carry prognostic significance and guide treatment. In addition to the well-known features, tumor budding (TB), poorly differentiated clusters (PDCs), and amount of stroma within the invasive front are associated with a poor prognostic outcome in many carcinomas. Here, we evaluate TB, PDCs, and the stroma percentage in UEC and correlate these findings with morphologic features known to be associated with a poor clinical outcome and with recurrence-free survival (RFS). We performed a retrospective search of our institution's EMR for cases of hysterectomy for UEC. We collected clinical data including disease recurrence, death, and data associated with poor patient outcomes. Cases were evaluated for TB, PDCs, and percent stroma by 2 pathologists. Ten 20× fields were examined, and the one with the most PDCs and TB was evaluated. Percent stroma was evaluated in a ×10 field of tumor at the area of deepest invasion. Less than 10% stroma was defined as stroma poor, and >10% stroma was defined as stroma rich. Statistical testing and analysis were conducted, and P-value was set at 0.05. One hundred thirteen cases were evaluated. Decreased RFS was seen with TB (P=0.03), at least 5 PDCs (P=0.01), and stroma-rich tumors (P=0.043). This study shows a statistically significant association between TB presence, at least 5 PDCs, stroma-rich tumors, and decreased RFS in UEC. We conclude that TB, PDCs and stromal evaluation are strong independent prognostic indicators in UEC and provide additional value to the currently used morphologic assessment of UEC.

Stroma-and Tumor-Associated Predictive Features in Salivary Gland Adenoid Cystic Carcinoma of the Head and Neck

BACKGROUND

There is lack of knowledge on the utility of prognostic histopathologic characteristics in adenoid cystic carcinoma (ACC) of the head and neck. We evaluated the prognostic value of tumor and stroma-related histopathologic features in ACC.

MATERIALS AND METHODS

A total of 65 cases of ACC from minor and major salivary glands were included in this study. We evaluated tumor budding, tumor-infiltrating lymphocytes (TILs), and tumor-stroma ratio (TSR) in hematoxylin and eosin (HE) stained sections.

RESULTS

Stroma-rich ACCs recurred more frequently (p = 0.029) during follow-up and associated with distant metastasis (p = 0.038). In multivariable analysis, stroma-rich tumors associated with poorer disease-specific survival with a hazard ratio of 3.76 (95% CI 1.10-12.83, p = 0.034). ACCs commonly showed a low infiltration of TILs as 89% of the tumors was characterized by an immune desert pattern. Low infiltration of TILs associated significantly with increased tumor budding (p = 0.039).

CONCLUSION

Adverse features of TSR and tumor budding are widely expressed in ACC, and stroma-rich tumors are associated with poor prognosis. Low number of TILs in ACC tissue indicates a weak immune response by the host and illustrates the nature of ACC as a relentless malignancy.

The predictive and prognostic value of tumor-stromal ratio and tumor budding in the recurrence and outcome of patients with oral tongue squamous cell carcinoma

INTRODUCTION

This study aimed to explore the predictive and prognostic value of tumor-stromal ratio (TSR) and tumor budding (TB) in the recurrence and outcome of patients with Oral tongue squamous cell carcinoma (OTSCC).

METHODS

All patients with OTSCC who underwent glossectomy with or without neck dissection in a tertiary center between 2010 and 2020 were included. The pathology slides of all patients were reviewed by a consulting pathologist. All pathologic features including tumor size, tumor grade, tumor thickness, surgical margin status, lymphovascular- and perineural invasion, T-stage, number of dissected, TB, TSR, and involved, tumor budding and tumor-stromal ratio were defined, we categorized the tumors as stroma-rich (low TSR) and stroma-poor (high TSR); as well as TB as low (0-4 buds) and high (≥ 5 buds). The inter-observer reliability of TB and TSR was assessed using the Kappa statistics analysis.

RESULTS

A total of 109 patients, with a median age of 62 (range 19-88) years, were included. There was a significant correlation between TSR and tumor budding with other adverse pathologic features and prognostic factors. In univariate analysis, both stromal-rich tumors and tumor budding were poor prognostic factors for disease-free survival (DFS) and overall survival (OS). However, on multivariate analysis, N-stage, adjuvant radiotherapy, tumor size, depth of invasion (DOI) and tumor budding emerged as independent prognostic factors for DFS. Likewise, N-stage, and DOI were recognized as independent prognostic factors for OS.

CONCLUSION

Both TSR and TB are important histopathological parameters strongly linked to other pathologic prognostic indicators. Additionally, they play key roles in predicting tumor behavior, recurrence, and patient survival.

Serous Ovarian Carcinoma: Detailed Analysis of Clinico-Pathological Characteristics as Prognostic Factors

BACKGROUND/OBJECTIVES

Serous ovarian carcinoma (SOC) is the most common subtype of epithelial ovarian cancer, with high-grade (HGSOC) and low-grade (LGSOC) subtypes presenting distinct clinical behaviours. This study aimed to evaluate histopathologic features in SOC, correlating these with prognostic outcomes, and explore the potential clinical implications.

METHODS

We analysed 51 SOC cases for lymphovascular space invasion (LVSI), tumour border configuration (TBC), microvessel density (MVD), tumour budding (TB), the tumour-stroma ratio (TSR), the stromal type, tumour-infiltrating lymphocytes (TILs), and tertiary lymphoid structures (TLSs). A validation cohort of 54 SOC cases from The Cancer Genome Atlas (TCGA) was used for comparison.

RESULTS

In the discovery set, significant predictors of aggressive behaviour included LVSI, high MVD, high TB, and low TILs. These findings were validated in the validation set where the absence of TLSs, lower peritumoural TILs, immature stromal type, and low TSR were associated with worse survival outcomes. The stromal type was identified as an independent prognostic predictor in SOC across both datasets. Inter-observer variability analysis demonstrated substantial to almost perfect agreement for these features, ensuring the reproducibility of the findings.

CONCLUSIONS

The histopathological evaluation of immune and stromal features, such as TILs, TLSs, TB, TSR, and stromal type, provides critical prognostic information for SOC. Incorporating these markers into routine pathological assessments could enhance risk stratification and guide treatment, offering practical utility, particularly in low-resource settings when molecular testing is not feasible.

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.

Tumour-stroma ratio (TSR) in breast cancer: comparison of scoring core biopsies versus resection specimens

PURPOSE

Tumour-stroma ratio (TSR) is an important prognostic and predictive factor in several tumour types. The aim of this study is to determine whether TSR evaluated in breast cancer core biopsies is representative of the whole tumour.

METHOD

Different TSR scoring methods, their reproducibility, and the association of TSR with clinicopathological characteristics were investigated in 178 breast carcinoma core biopsies and corresponding resection specimens. TSR was assessed by two trained scientists on the most representative H&E-stained digitised slides. Patients were treated primarily with surgery between 2010 and 2021 at Semmelweis University, Budapest.

RESULTS

Ninety-one percent of the tumours were hormone receptor (HR)-positive (luminal-like). Interobserver agreement was highest using 100 × magnification (κcore = 0.906, κresection specimen = 0.882). The agreement between TSR of core biopsies and resection specimens of the same patients was moderate (κ = 0.514). Differences between the two types of samples were most frequent in cases with TSR scores close to the 50% cut-off point. TSR was strongly correlated with age at diagnosis, pT category, histological type, histological grade, and surrogate molecular subtype. A tendency was identified for more recurrences among stroma-high (SH) tumours (p = 0.07). Significant correlation was detected between the TSR and tumour recurrence in grade 1 HR-positive breast cancer cases (p = 0.03).

CONCLUSIONS

TSR is easy to determine and reproducible on both core biopsies and in resection specimens and is associated with several clinicopathological characteristics of breast cancer. TSR scored on core biopsies is moderately representative for the whole tumour.

Extracellular vesicles from cancer cell lines of different origins drive the phenotype of normal oral fibroblasts in a CAF-like direction

Introduction

Normal oral fibroblasts (NOFs) are located in the connective tissue of the oral mucosa. The NOFs play an important role in wound healing, tumor progression, and metastasis. They are subjected to influence by external and internal stimuli, among them extracellular vesicles (EVs), that are considered as important players in cell to cell communication, especially in carcinogenesis and metastatic processes. During tumorigenesis, stromal NOFs may undergo activation into cancer-associated fibroblasts (CAFs) that modify their phenotype to provide pro-oncogenic signals that in turn facilitate tumor initiation, progression, and metastasis. The aim of the study was to reveal the effect of EVs derived from local (oral squamous cell carcinoma - OSCC) and distant (pancreatic adenocarcinoma - PDAC; malignant melanoma brain metastasis - MBM) cancer origin on NOFs and their possible change into a CAF-like direction.

Methods

The effect of each of the cancer EV types on NOFs proliferation, viability, and migration was tested. Also, changes in gene expression of the well-established CAF biomarkers ACTA2, FAP, PDGFR, and two putative CAF biomarkers, the Ca2+- activated ion channels ANO1 and KCNMA, were studied.

Results

Obtained results indicate that NOFs receive and process signals transmitted by EVs originating from both OSCC, PDAC, and MBM. The fibroblast response was dependent on EV origin and concentration, and duration of EV exposure.

Conclusion

The present results indicate that the molecular cargo of the EVs direct NOFs towards a pro-tumorigenic phenotype.

A Novel Artificial Intelligence-Based Parameterization Approach of the Stromal Landscape in Merkel Cell Carcinoma: A Multi-Institutional Study

Tumor-stroma ratio (TSR) has been recognized as a valuable prognostic indicator in various solid tumors. This study aimed to examine the clinicopathologic relevance of TSR in Merkel cell carcinoma (MCC) using artificial intelligence (AI)-based parameterization of the stromal landscape and validate TSR scores generated by our AI model against those assessed by humans. One hundred twelve MCC cases with whole-slide images were collected from 4 different institutions. Whole-slide images were first partitioned into 128 × 128-pixel "mini-patches," then classified using a novel framework, termed pre-tumor and stroma (Pre-TOAST) and TOAST, whose output equaled the probability of the minipatch representing tumor cells rather than stroma. Hierarchical random samplings of 50 minipatches per region were performed throughout 50 regions per slide. TSR and tumor-stroma landscape (TSL) parameters were estimated using the maximum-likelihood algorithm. Receiver operating characteristic curves showed that the area under the curve value of Pre-TOAST in discriminating classes of interest including tumor cells, collagenous stroma, and lymphocytes from nonclasses of interest including hemorrhage, space, and necrosis was 1.00. The area under the curve value of TOAST in differentiating tumor cells from related stroma was 0.93. MCC stroma was categorized into TSR high (TSR ≥ 50%) and TSR low (TSR < 50%) using both AI- and human pathology-based methods. The AI-based TSR-high subgroup exhibited notably shorter metastasis-free survival (MFS) with a statistical significance of P = .029. Interestingly, pathologist-determined TSR subgroups lacked statistical significance in recurrence-free survival, MFS, and overall survival (P > .05). Density-based spatial clustering of applications with noise analysis identified the following 2 distinct TSL clusters: TSL1 and TSL2. TSL2 showed significantly shorter recurrence-free survival (P = .045) and markedly reduced MFS (P < .001) compared with TSL1. TSL classification appears to offer better prognostic discrimination than traditional TSR evaluation in MCC. TSL can be reliably calculated using an AI-based classification framework and predict various prognostic features of MCC.

Immune cell distribution and DNA methylation signatures differ between tumor and stroma enriched compartment in pancreatic ductal adenocarcinoma

The presence of abundant tumor stroma is a prominent characteristic of pancreatic ductal adenocarcinomas (PDAC) that potentially influences disease progression and therapy response. This study aims to investigate immune cell infiltration and epigenetic profiles in tumor cell enriched ("Tumor") and stroma cell enriched ("Stroma") regions within human PDAC tissue samples. By comparing those regions, we identified 25,410 differentially methylated positions (DMPs) distributed across 6,963 unique genes. Pathway enrichment analysis using the top 2,000 DMPs that were either hyper- or hypomethylated indicated that immune response pathways and the estrogen receptor pathway are epigenetically dysregulated in Tumor and Stroma regions, respectively. In terms of immune cell infiltration, we observed overall low levels of T cells in both regions. In Tumor regions however, occurrence of tumor-associated macrophages (TAMs) was higher than in Stroma regions (p = 0.02) concomitant with a dualistic distribution that stratifies PDAC patients into those with high and low TAM infiltration. By categorizing TAM levels into quartiles, our analysis revealed that PDAC patients with more than 1,515 TAMs per mm² exhibited significantly shorter overall survival (p = 0.036). Our data suggest that variations in inflammatory characteristics between the Tumor and Stroma defined compartments of PDAC may primarily stem from the presence of macrophages rather than lymphocytes. The abundance of TAMs within regions enriched with tumor cells correlates with patient survival, underscoring the potential significance of exploring therapeutic interventions targeting TAMs. Furthermore, directing attention towards the estrogen receptor pathway may represent a promising strategy to address the stroma cell component within the PDAC tumor microenvironment.

Digital Whole Slide Image Analysis of Elevated Stromal Content and Extracellular Matrix Protein Expression Predicts Adverse Prognosis in Triple-Negative Breast Cancer

Triple-negative breast cancer (TNBC) is a subtype of breast cancer with a poor prognosis and limited treatment options. This study evaluates the prognostic value of stromal markers in TNBC, focusing on the tumor-stroma ratio (TSR) and overall stroma ratio (OSR) in whole slide images (WSI), as well as the expression of type-I collagen, type-III collagen, and fibrillin-1 on tissue microarrays (TMAs), using both visual assessment and digital image analysis (DIA). A total of 101 female TNBC patients, primarily treated with surgery between 2005 and 2016, were included. We found that high visual OSR correlates with worse overall survival (OS), advanced pN categories, lower stromal tumor-infiltrating lymphocyte count (sTIL), lower mitotic index, and patient age (p < 0.05). TSR showed significant connections to the pN category and mitotic index (p < 0.01). High expression levels of type-I collagen (>45%), type-III collagen (>30%), and fibrillin-1 (>20%) were linked to significantly worse OS (p = 0.004, p = 0.013, and p = 0.005, respectively) and progression-free survival (PFS) (p = 0.028, p = 0.025, and p = 0.002, respectively), validated at the mRNA level. Our results highlight the importance of stromal characteristics in promoting tumor progression and metastasis and that targeting extracellular matrix (ECM) components may offer novel therapeutic strategies. Furthermore, DIA can be more accurate and objective in evaluating TSR, OSR, and immunodetected stromal markers than traditional visual examination.

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.

Comparison of the 7th and revised 8th UICC editions (2020) for oral squamous cell carcinoma: How does the reclassification impact staging and survival?

Since its introduction in 1968, the TNM (tumor, node, metastasis) classification established by the International Union Against Cancer has provided a consistent framework for staging of oral squamous cell carcinoma (OSCC). The introduction of the 8th edition in 2017 brought about significant modifications, encompassing the integration of depth of invasion (DOI) and extranodal extension (ENE) into the T and N classifications. Further, the UICC the criteria for the T3 and T4a categories were amended in 2020. This study aimed to evaluate the impact of reclassification on staging and, subsequently, the survival of patients with OSCC. Primary OSCCs from 391 patients were classified according to the 7th and revised 8th UICC editions (2020). Stage migration was assessed, and stage-specific progression-free survival (PFS) and overall survival (OS) were evaluated using the Kaplan-Meier method. The log-rank test was used to compare the different stages. Cox-proportional hazard modeling was used to compare the two editions. Incorporating the DOI into the T classification resulted in an upstaging of 77 patients, constituting 19.69% of the cohort. In addition, 49 (12.53%) patients experienced an upstaging when considering ENE in the N classification. Consequently, 103 patients underwent upstaging in UICC staging, accounting for 21.74% of cases. Upstaging mainly occurred from stage III to IVA (26.92%) and from stage IVA to IVB (31.78%). Upon comparing the categories in survival analysis, significant differences in OS and PFS were especially observed between stage IVB and lower stages. When examining the hazard ratios, it became evident that UICC 8 stage IVB is burdened by a 5.59-fold greater risk of disease progression than stage I. Furthermore, UICC 8 stage IVB exhibits a 3.83 times higher likelihood of death than stage I disease. We demonstrated significant stage migration from the 7th to the revised 8th UICC edition. Overall, incorporating DOI and ENE into the T and N classifications represents a substantial clinical advancement, leading to a more accurate staging of OSCC patients. Both staging systems exhibited statistically significant discrimination between stages; however, the 8th UICC edition allowed for a more precise categorization of patients based on their prognosis and led to enhanced hazard discrimination, particularly within higher stages.

Artificial intelligence in digital histopathology for predicting patient prognosis and treatment efficacy in breast cancer

INTRODUCTION

Histological images contain phenotypic information predictive of patient outcomes. Due to the heavy workload of pathologists, the time-consuming nature of quantitatively assessing histological features, and human eye limitations to recognize spatial patterns, manually extracting prognostic information in routine pathological workflows remains challenging. Digital pathology has facilitated the mining and quantification of these features utilizing whole-slide image (WSI) scanners and artificial intelligence (AI) algorithms. AI algorithms to identify image-based biomarkers from the tumor microenvironment (TME) have the potential to revolutionize the field of oncology, reducing delays between diagnosis and prognosis determination, allowing for rapid stratification of patients and prescription of optimal treatment regimes, thereby improving patient outcomes.

AREAS COVERED

In this review, the authors discuss how AI algorithms and digital pathology can predict breast cancer patient prognosis and treatment outcomes using image-based biomarkers, along with the challenges of adopting this technology in clinical settings.

EXPERT OPINION

The integration of AI and digital pathology presents significant potential for analyzing the TME and its diagnostic, prognostic, and predictive value in breast cancer patients. Widespread clinical adoption of AI faces ethical, regulatory, and technical challenges, although prospective trials may offer reassurance and promote uptake, ultimately improving patient outcomes by reducing diagnosis-to-prognosis delivery delays.

Comparison of mismatch repair and immune checkpoint protein profile with histopathological parameters in pancreatic, periampullary/ampullary, and choledochal adenocarcinomas

BACKGROUND

Pancreatic, periampullary/ampullary, and choledochal adenocarcinomas are aggressive malignancies with a poor prognosis. Immune checkpoint blockade is a promising treatment option for several tumor types. H long terminal repeat-associating 2 (HHLA2), which is analogous to programmed death-ligand 1 (PD-L1), is a recently discovered member of the B7/cluster of differentiation 28 family and is expressed in many malignancies.

AIM

To analyze the expression of HHLA2 and its association with the pathologic biomarkers that predict sensitivity to immunotherapy.

METHODS

Ninety-two adenocarcinoma cases located in the pancreas, ampulla, and distal common bile duct were identified. This study assessed 106 pancreaticoduodenectomy and distal/total pancreatectomy samples that were delivered to Ankara City Hospital between 2019 and 2021. Immunohistochemistry was conducted to examine the expression of DNA mismatch repair (MMR), PD-L1, and HHLA2 proteins.

RESULTS

Patients with high HHLA2 expression had a higher mean age than those with low expression. Low HHLA2 expression was associated with high perineural invasion. HHLA2 expression was low in pathological stage T3 (pT) 3 cases and high in pathological stage T1, T2, and T4 cases. There was no correlation between HHLA2 expression and the expression of MMR proteins and PD-L1.

CONCLUSION

Evaluation of HHLA2 expression in microsatellite stable and PD-L1-negative tumors may be useful for predicting the response of individuals to immunotherapy and may serve as a novel therapeutic target for immunotherapy in advanced-stage disease.

A Mathematical Model of Stroma-Supported Allometric Tumor Growth

Mounting empirical research suggests that the stroma, or interface between healthy and cancerous tissue, is a critical determinate of cancer invasion. At the same time, a cancer cell's location and potential to proliferate can influence its sensitivity to cancer treatments. In this paper, we use ordinary differential equations to develop spatially structured models for solid tumors wherein the growth of tumor components is coordinated. The model tumors feature two components, a proliferating peripheral growth region, which potentially includes a mix of cancerous and noncancerous stroma cells, and a solid tumor core. Mathematical and numerical analysis are used to investigate how coordinated expansion of the tumor growth region and core can influence overall growth dynamics in a variety of tumor types. Model assumptions, which are motivated by empirical and in silico solid tumor research, are evaluated through comparison to tumor volume data and existing models of tumor growth.

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.

Influence of Tumor Stroma on the Aggressiveness of Poorly Cohesive Gastric Carcinoma

Tumor-stroma crosstalk promotes the adaptation of cancer cells to the local microenvironment and sustains their growth. We assessed the quantitative and qualitative impact of intralesional stroma on clinic-pathological features and the prognosis of poorly cohesive gastric cancer (PCGC) variants. Tissue microarrays including 75 PCGC specimens were immunostained for cytokeratin 8/18 and α-smooth muscle actin to assess the relative proportion of neoplastic cells versus stromal components and the cases were subsequently divided into stroma-rich (SR) and stroma-poor (SP) tumors. Stromal status is significantly associated with the depth of tumor invasion. Patient survival rate was found to be higher in the SP compared to the SR tumor group and, hence, abundant stroma was identified as a significant risk factor in univariable analysis but had no independent prognostic impact. We also investigated the mRNA levels of KRT8 and the associated transcriptional signatures using the molecular data of 82 PCGC cases divided into KRT8-high and KRT8-low groups. KRT8-high tumors were enriched in proteins localized in the extracellular compartment and their expression levels correlated with longer survival in the KRT8-high group and shorter overall survival in the KRT8-low group. Comprehensively, we find that relative intralesional stromal content is a marker of aggressiveness in PCGC tumors and that extracellular proteins characterize functionally and clinically different PCGC subgroups.

A Correlation of Tumour Budding and Tumour-Stroma Ratio with Clinicopathological Factors in Oral Squamous Cell Carcinoma

Objectives

This study aimed to analyse the association of tumour budding (TB) and tumour-stroma ratio (TSR) with clinicopathological parameters that can be easily viewed on routine haematoxylin and eosin (H&E)-stained slides to provide an easy and cost-effective method for prognosticating oral squamous cell carcinoma (OSCC).

Methods

This study was conducted at the ESIC Medical College and Hospital in Faridabad, India, from July 2022 to October 2022. In patients with histologically diagnosed OSCC, TB and TSR were evaluated via routine H&E-stained sections and correlated with clinicopathological parameters. Statistical analysis was performed using Chi-squared test.

Results

A total of 50 patients were included. The mean age of participants was 61 ± 12.72, and the male-to-female ratio was 7.1:1. Most of the tumours were located on the tongue (46%), followed by the buccal mucosa (26%), gingivobuccal sulcus (12%) and retromolar trigone (8%). The palate and alveolus were the other sites involved, constituting 4% each. TB and TSR were both found to be significantly associated with the tumour grade, lymph node metastasis and tumour size. A highly significant correlation was also found between TB and TSR (P = 0.001).

Conclusions

Both TB and TSR can be easily evaluated on routine H&E sections; they are highly reproducible and were found to be reliable independent prognostic markers in OSCC. Therefore, this simple and cost-effective method of prognostication, which is currently lacking in clinical practice, will help clinicians to identify patients with poor prognosis and thus individualise their treatment plan.

Cancer-Associated Fibroblasts in Esophageal Cancer

Cancer-associated fibroblasts (CAFs), a heterogenous population, can promote cancer cell proliferation, migration, invasion, immunosuppression, and therapeutic resistance in solid tumors. These effects are mediated through secretion of cytokines and growth factors, remodeling of the extracellular matrix, and providing metabolic support for cancer cells. The presence of CAFs in esophageal carcinoma are associated with reduced overall survival and increased resistance to chemotherapy and radiotherapy; thus, identifying therapeutic vulnerabilities of CAFs is a necessity. In esophageal cancer, the mechanisms for CAF recruitment, CAF-mediated promotion of tumorigenesis, metastatic dissemination, and therapeutic resistance have yet to be fully evaluated. Here, we provide an overview of the current understanding of CAFs in esophageal cancer, namely in esophageal squamous cell carcinoma and esophageal adenocarcinoma, as well as in the preneoplastic conditions that predispose to these cancers. Interestingly, there is a discrepancy in our knowledge of CAF biology between esophageal cancer subtypes, with very few studies in esophageal adenocarcinoma, and its precursor lesion Barrett's esophagus, compared with esophageal squamous cell carcinoma. We propose that although great strides have been made, certain questions remain to which answers hopefully will emerge to have an impact on biomarker diagnostics and translational therapeutics.

Cell membrane-anchored and tumor-targeted IL-12 T-cell therapy destroys cancer-associated fibroblasts and disrupts extracellular matrix in heterogenous osteosarcoma xenograft models

BACKGROUND

The extracellular matrix (ECM) and cancer-associated fibroblasts (CAFs) play major roles in tumor progression, metastasis, and the poor response of many solid tumors to immunotherapy. CAF-targeted chimeric antigen receptor-T cell therapy cannot infiltrate ECM-rich tumors such as osteosarcoma.

METHOD

In this study, we used RNA sequencing to assess whether the recently invented membrane-anchored and tumor-targeted IL-12-armed (attIL12) T cells, which bind cell-surface vimentin (CSV) on tumor cells, could destroy CAFs to disrupt the ECM. We established an in vitro model of the interaction between osteosarcoma CAFs and attIL12-T cells to uncover the underlying mechanism by which attIL12-T cells penetrate stroma-enriched osteosarcoma tumors.

RESULTS

RNA sequencing demonstrated that attIL12-T cell treatment altered ECM-related gene expression. Immunohistochemistry staining revealed disruption or elimination of high-density CAFs and ECM in osteosarcoma xenograft tumors following attIL12-T cell treatment, and CAF/ECM density was inversely correlated with T-cell infiltration. Other IL12-armed T cells, such as wild-type IL-12-targeted or tumor-targeted IL-12-T cells, did not disrupt the ECM because this effect depended on the engagement between CSV on the tumor cell and its ligand on the attIL12-T cells. Mechanistic studies found that attIL12-T cell treatment elevated IFNγ production on interacting with CSV+ tumor cells, suppressing transforming growth factor beta secretion and in turn upregulating FAS-mediated CAF apoptosis. CAF destruction reshaped the tumor stroma to favor T-cell infiltration and tumor inhibition.

CONCLUSIONS

This study unveiled a novel therapy-attIL12-T cells-for targeting CAFs/ECM. These findings are highly relevant to humans because CAFs are abundant in human osteosarcoma.

Engineering dense tumor constructs via cellular contraction of extracellular matrix hydrogels

Physical characteristics of solid tumors such as dense internal microarchitectures and pathological stiffness influence cancer progression and treatment. While it is routine to engineer culture substrates and scaffolds with elastic moduli that approximate tumors, these models often fail to capture characteristic internal microarchitectures such as densely compacted concentric ECM fibers at the stromal interface. Contractile mesenchymal cells can solve this engineering challenge by deforming, contracting, and compacting extracellular matrix (ECM) hydrogels to decrease tissue volume and increase tissue density. Here we demonstrate that allowing human fibroblasts of varying origins to freely contract collagen type I-containing hydrogels co-seeded with carcinoma cell spheroids produces a tissue engineered construct with structural features that mimic dense solid tumors in vivo. Morphometry and mechanical testing were conducted in tandem with biochemical analysis of proliferation and viability to confirm that dense carcinoma constructs engineered using this approach capture relevant physical characteristics of solid carcinomas in a tractable format that preserves viability and is amenable to extended culture. The reported method is adaptable to the use of multiple mesenchymal cell types and the inclusion of fibrin in the ECM combined with seeding of endothelial cells to produce prevascularized constructs. The physical dense carcinoma constructs engineered using this approach may provide more clinically relevant venues for studying cancer pathophysiology and the challenges associated with the delivery of macromolecular drugs and cellular immunotherapies to solid tumors.

The prognostic value of tumor-stroma ratio and a newly developed computer-aided quantitative analysis of routine H&amp;E slides in high-grade serous ovarian cancer

INTRODUCTION

Tumor-stroma ratio (TSR) is prognostic in multiple cancers, while its role in high-grade serous ovarian cancer (HGSOC) remains unclear. Despite the prognostic insight gained from genetic profiles and tumor-infiltrating lymphocytes (TILs), the prognostic use of histology slides remains limited, while it enables the identification of tumor characteristics via computational pathology reducing scoring time and costs. To address this, this study aimed to assess TSR's prognostic role in HGSOC and its association with TILs. We additionally developed an algorithm, Ovarian-TSR (OTSR), using deep learning for TSR scoring, comparing it to manual scoring. Methods : 340 patients with advanced-stage who underwent primary debulking surgery (PDS) or neo-adjuvant chemotherapy (NACT) with interval debulking (IDS). TSR was assessed in both the most invasive (MI) and whole tumor (WT) regions through manual scoring by pathologists and quantification using OTSR. Patients were categorized as stroma-rich (≥ 50% stroma) or stroma-poor (< 50%). TILs were evaluated via immunohistochemical staining. Result s: In PDS, stroma-rich tumors were significantly associated with a more frequent papillary growth pattern (60% vs 34%), while In NACT stroma-rich tumors had a lower Tumor Regression Grading (TRG 4&5, 21% vs 57%) and increased pleural metastasis (25% vs 16%). Stroma-rich patients had significantly shorter overall and progression-free survival compared to stroma-poor (31 versus 45 months; P < 0.0001, and 15 versus 17 months; P = 0.0008, respectively). Combining stromal percentage and TILs led to three distinct survival groups with good (stroma-poor, high TIL), medium (stroma-rich, high TIL, or; stroma-poor, Low TIL), and poor(stroma-rich, low TIL) survival. These survival groups remained significant in CD8 and CD103 in multivariable analysis (Hazard ratio (HR) = 1.42, 95% Confidence-interval (CI) = 1.02-1.99; HR = 1.49, 95% CI = 1.01-2.18, and HR = 1.48, 95% CI = 1.05-2.08; HR = 2.24, 95% CI = 1.55-3.23, respectively). OTSR was able to recapitulate these results and demonstrated high concordance with expert pathologists (correlation = 0.83). Conclusions : TSR is an independent prognostic factor for survival assessment in HGSOC. Stroma-rich tumors have a worse prognosis and, in the case of NACT, a higher likelihood of pleural metastasis. OTSR provides a cost and time-efficient way of determining TSR with high reproducibility and reduced inter-observer variability.

Theranostics in targeting fibroblast activation protein bearing cells: Progress and challenges

Cancer cells are surrounded by a complex and highly dynamic tumor microenvironment (TME). Cancer-associated fibroblasts (CAFs), a critical component of TME, contribute to cancer cell proliferation as well as metastatic spread. CAFs express a variety of biomarkers, which can be targeted for detection and therapy. Most importantly, CAFs express high levels of fibroblast activation protein (FAP) which contributes to progression of cancer, invasion, metastasis, migration, immunosuppression, and drug resistance. As a consequence, FAP is an attractive theranostic target. In this review, we discuss the latest advancement in targeting FAP in oncology using theranostic biomarkers and imaging modalities such as single-photon emission computed tomography (SPECT), positron emission tomography (PET), computed tomography (CT), fluorescence imaging, and magnetic resonance imaging (MRI).

Independent Tissue-Based Biomarkers in Endometrioid Endometrial Cancer: Tumor Budding in Microsatellite Instability and WHO Grading in Copy-Number-Low Patients

The molecular characterization of endometrial endometrioid adenocarcinomas has provided major advances in its prognostic stratification. However, risk assessment of microsatellite instability (MSI) and copy-number (CN)-low cases remains a challenge. Thus, we aimed to identify tissue-based morphologic biomarkers that might help in the prognostic stratification of these cases. Histomorphologic parameters (WHO grading, tumor budding (TB), tumor-stroma ratio (as a quantitative description of stromal desmoplasia), tumor-infiltrating lymphocytes (TIL), "microcystic, elongated, fragmented" (MELF) pattern) were analyzed in resection specimens of the TCGA-UCEC cohort (n = 228). For each quantitative parameter, a two-tiered system was developed utilizing systematically determined cutoffs. Associations with survival outcomes were calculated in univariate and multivariate analysis and validated in two independent cohorts. In MSI tumors, only TB remained an independent prognostic factor. TB (≥3 buds/high-power field) was associated with inferior outcomes and with lymph node metastases. The prognostic significance of TB was confirmed in two validation cohorts. For CN-low tumors, established grading defined by the WHO was independently prognostic with inferior outcomes for high-grade tumors. The evaluation of TB might help in identifying MSI-patients with unfavorable prognosis who, e.g., could benefit from lymphadenectomy. WHO-based grading facilitates independent prognostic stratification of CN-low endometrioid adenocarcinomas. Therefore, we propose the utilization of TB and WHO-based grading, two tissue-based and easy-to-assess biomarkers, in MSI/CN-low endometrial carcinomas for improved clinical management.

Stereotactic Body Radiation Therapy in Gynecologic Oligometastases: An Effective but Underutilized Approach

Historically, the role of radiation in gynecological metastatic disease involved palliation for pain or bleeding. Stereotactic Body Radiation Therapy (SBRT) has shown survival benefits in oligometastatic disease from varying primary histologies in recent randomized trials. However, gynecologic primary oligometastases have been underrepresented in these trials. Recent studies across gynecological malignancy types have similarly shown favorable outcomes and acceptable toxicities from treating recurrent or oligometastatic gynecologic cancer (ROMGC) patients with definitive radiation therapy. The largest body of literature reported on the use of SBRT in ovarian cancer, which was found to be an effective option, especially in the setting of chemo-resistant disease. Despite the encouraging outcomes using SBRT in oligometastatic gynecologic malignancies, SBRT remains underutilized given the lack of randomized studies studying ROMGC with long term follow-up. While waiting for future prospective trials to establish the role of SBRT as the standard of care in ROMGC patients, this review focuses on reporting the advantages and drawbacks of this technique and examines the current literature to help guide patient centered treatment decisions.

The prognostic role of tumor budding and tumor-stroma ratio in pulmonary metastasis of colorectal carcinoma

OBJECTIVE

To evaluate the prognostic value of tumor budding and tumor-stroma ratio (TSR) in resected pulmonary metastases of colorectal carcinoma (CRC).

METHODS

In total, 106 pulmonary metastasectomies were performed to 74 patients in two study hospitals during 2000-2020. All relevant clinical data were retrospectively collected. Tumor budding based on the International Tumor Budding Consensus Conference recommendations and TSR in the first resected pulmonary metastases and primary tumors were evaluated from diagnostic hematoxylin-eosin-stained histopathological slides.

RESULTS

60 patients (85.7%) had low tumor budding (≤5 buds/field) and 10 patients (14.3%) had high tumor budding (>5 buds/field) in their first pulmonary metastases of CRC. 5-year overall survival rates of pulmonary metastasectomy in low and high total tumor budding were 28.3% and 37.3% (p = 0.387), respectively. 19 patients (27.1%) had low TSR and 51 patients (72.9%) had high TSR. The 5-year overall survival rates were 32.9% in low and 28.6% in high TSR of first pulmonary metastases (p = 0.746). Tumor budding and TSR did not provide prognostic value in Cox multivariate analysis. Tumor budding and TSR in resected pulmonary metastases were not associated with those of the primary tumor.

CONCLUSION

Tumor budding and TSR in the resected pulmonary metastases of CRC showed no statistically significant prognostic value, however, additional well-powered confirmatory studies are needed.

Preliminary study of some of the main intratumor stroma components in gastric carcinomas

AIM

The relationship between stromal compartment and tumor behavior in gastric carcinomas is still poorly understood and defined. Therefore, the authors started, with this preliminary study, an analysis of stromal compartment morphology and behavior in tumors arising from gastric mucosa epithelium.

MATERIALS AND METHODS

The study group included 75 patients operated for gastric carcinoma. Five parameters describing tumor morphology and behavior and eight parameters describing tumor stroma (TS) morphology were assessed. Histopathological examination included six serial sections of formalin-fixed, paraffin-embedded tumor tissue samples, stained with three classical stains and three antibodies to reveal the different parameters. For data comparison, Pearson's correlation test and the chi-squared (χ²) correlation test were used.

RESULTS

Studied tumors were, usually, infiltrating, undifferentiated∕diffuse type, invasive in subserous spaces and with a Ki67 index higher than 20%. Collagen fibers dominated the stromal components, with a predominance of mature type and an average fibrillary index of 2.7. The whole amount of stromal components accounted for around one quarter of the tumor area. Mature collagen fibers were in opposite correlation with their immature counterpart, and both were in opposite correlation with smooth muscle fibers and expressed an opposite trend of correlation with components of vascular compartment. The whole amount of stromal components had divergent behavior with the components of vascular compartment. The latter expressed generally an opposite trend of correlation with individual fibrillary stromal components. We found only isolated relationships statistically significant between stromal components and tumor characteristics.

CONCLUSIONS

TS is in a continuous remodeling process in relation to the evolution of tumor parenchyma, tumors less differentiated proving to have an immature stroma, with newly formed collagen fibers and higher vascular density. Further studies are required.

Clinical predictors and outcomes of non-expandable lung following percutaneous catheter drainage in lung cancer patients with malignant pleural effusion

Non-expandable lung (NEL) often occurs during pleural fluid drainage in patients with malignant pleural effusion (MPE). However, data regarding the predictors and prognostic impact of NEL on primary lung cancer patients with MPE receiving pleural fluid drainage, compared to malignant pleural mesothelioma (MPM), are limited. This study was aimed to investigate the clinical characteristics of lung cancer patients with MPE developing NEL following ultrasonography (USG)-guided percutaneous catheter drainage (PCD) and compare the clinical outcomes between those with and without NEL. Clinical, laboratory, pleural fluid, and radiologic data and survival outcomes of lung cancer patients with MPE undergoing USG-guided PCD were retrospectively reviewed and compared between those with and without NEL. Among 121 primary lung cancer patients with MPE undergoing PCD, NEL occurred in 25 (21%). Higher pleural fluid lactate dehydrogenase (LDH) levels and presence of endobronchial lesions were associated with development of NEL. The median time to catheter removal was significantly extended in those with NEL compared to those without (P = .014). NEL was significantly associated with poor survival outcome in lung cancer patients with MPE undergoing PCD, along with poor Eastern Cooperative Oncology Group (ECOG) performance status (PS), the presence of distant metastasis, higher serum C-reactive protein (CRP) levels, and not receiving chemotherapy. NEL developed in one-fifth of lung cancer patients undergoing PCD for MPE and was associated with high pleural fluid LDH levels and the presence of endobronchial lesions. NEL may negatively affect overall survival in lung cancer patients with MPE receiving PCD.

Chronic Obstructive Pulmonary Disease Is Associated with Worse Oncologic Outcomes in Early-Stage Resected Pancreatic and Periampullary Cancers

Pancreatic ductal adenocarcinoma (PDAC) is the 3rd leading cause of cancer mortality in the United States. Hypoxic and hypercapnic tumor microenvironments have been suggested to promote tumor aggressiveness. The objective of this study was to evaluate the association between chronic obstructive pulmonary disease (COPD) and oncologic survival outcomes in patients with early-stage PDAC and periampullary cancers. In this case-control study, patients who underwent a pancreaticoduodenectomy during 2014-2021 were assessed. Demographic, perioperative, histologic, and oncologic data were collected. A total of 503 PDAC and periampullary adenocarcinoma patients were identified, 257 males and 246 females, with a mean age of 68.1 (±9.8) years and a mean pre-operative BMI of 26.6 (±4.7) kg/m². Fifty-two percent of patients (N = 262) reported a history of smoking. A total of 42 patients (8.3%) had COPD. The average resected tumor size was 2.9 ± 1.4 cm and 65% of the specimens (N = 329) were positive for lymph-node involvement. Kaplan-Meier analysis showed that COPD was associated with worse overall and disease-specific survival (p < 0.05). Cox regression analysis showed COPD to be an independent prognostic factor (HR = 1.5, 95% CI 1.0-2.3, p = 0.039) along with margin status, lymphovascular invasion, and perineural invasion (p < 0.05 each). A 1:3 nearest neighbor propensity score matching was also employed and revealed COPD to be an independent risk factor for overall and disease-specific survival (OR 1.8 and OR 1.6, respectively; p < 0.05 each). These findings may support the rationale posed by in vitro laboratory studies, suggesting an important impact of hypoxic and hypercapnic tumor respiratory microenvironments in promoting therapy resistance in cancer.

Autologous dendritic cells loaded with antigens from self-renewing autologous tumor cells as patient-specific therapeutic cancer vaccines

A promising personal immunotherapy is autologous dendritic cells (DC) loaded ex vivo with autologous tumor antigens (ATA) derived from self-renewing autologous cancer cells. DC-ATA are suspended in granulocyte-macrophage colony stimulating factor at the time of each subcutaneous injection. Previously, irradiated autologous tumor cell vaccines have produced encouraging results in 150 cancer patients, but the DC-ATA vaccine demonstrated superiority in single-arm and randomized trials in metastatic melanoma. DC-ATA have been injected into more than 200 patients with melanoma, glioblastoma, and ovarian, hepatocellular, and renal cell cancers. Key observations include: [1] greater than 95% success rates for tumor cell cultures and monocyte collection for dendritic cell production; [2] injections are well-tolerated; [3] the immune response is rapid and includes primarily TH1/TH17 cellular responses; [4] efficacy has been suggested by delayed but durable complete tumor regressions in patients with measurable disease, by progression-free survival in glioblastoma, and by overall survival in melanoma.

Immune modulations of the tumor microenvironment in response to phototherapy

The tumor microenvironment (TME) promotes pro-tumor and anti-inflammatory metabolisms and suppresses the host immune system. It prevents immune cells from fighting against cancer effectively, resulting in limited efficacy of many current cancer treatment modalities. Different therapies aim to overcome the immunosuppressive TME by combining various approaches to synergize their effects for enhanced anti-tumor activity and augmented stimulation of the immune system. Immunotherapy has become a major therapeutic strategy because it unleashes the power of the immune system by activating, enhancing, and directing immune responses to prevent, control, and eliminate cancer. Phototherapy uses light irradiation to induce tumor cell death through photothermal, photochemical, and photo-immunological interactions. Phototherapy induces tumor immunogenic cell death, which is a precursor and enhancer for anti-tumor immunity. However, phototherapy alone has limited effects on long-term and systemic anti-tumor immune responses. Phototherapy can be combined with immunotherapy to improve the tumoricidal effect by killing target tumor cells, enhancing immune cell infiltration in tumors, and rewiring pathways in the TME from anti-inflammatory to pro-inflammatory. Phototherapy-enhanced immunotherapy triggers effective cooperation between innate and adaptive immunities, specifically targeting the tumor cells, whether they are localized or distant. Herein, the successes and limitations of phototherapy combined with other cancer treatment modalities will be discussed. Specifically, we will review the synergistic effects of phototherapy combined with different cancer therapies on tumor elimination and remodeling of the immunosuppressive TME. Overall, phototherapy, in combination with other therapeutic modalities, can establish anti-tumor pro-inflammatory phenotypes in activated tumor-infiltrating T cells and B cells and activate systemic anti-tumor immune responses.

Tumor-Stroma Ratio in Basaloid and Conventional Laryngeal Squamous Cell Carcinoma: Prognostic Significance and Concordance in Paired Biopsies and Surgical Samples

Basaloid squamous cell carcinoma (BSCC) is a subtype of squamous cell carcinoma (SCC) associated with a poor prognosis. Tumor–stroma ratio (TSR) has been introduced as a prognostic feature in many solid tumors. TSR was investigated in a series of laryngeal BSCCs and compared with a group of stage-matched conventional SCCs (cSCCs), in both preoperative and surgical specimens, with the intent of ascertaining the more aggressive behavior of BSCC and verifying the presence of stromal-related causes. A series of 14 consecutive laryngeal BSCCs and a control group of 28 stage-matched conventional cSCCs were analyzed. A higher nodal metastasis presence was found in BSCCs (57.1% vs. 28.6%). The recurrence rate was 33.5% and 63.6% in the cSCC and BSCC groups; disease-free survival (DFS) was higher, though not significantly, in patients with cSCC. TSR, large cell nests, and tumor budding showed a moderate to very good agreement, and stroma type a good to very good agreement between biopsies and surgical specimens in the cSCC group. In the BSCC group, agreement was poor to very good for TSR and stroma type, and good to very good for large cell nests and tumor budding. Age was the only feature significant in predicting recurrence in the BSCC group (p = 0.0235). In cSCC, TSR low/stroma rich cases, when evaluated on biopsies or surgical specimens, were associated with lower DFS (p = 0.0036; p = 0.0041, respectively). Laryngeal BSCCs showed a lower DFS than cSCCs, even if statistical significance was not reached. TSR, evaluated in laryngeal biopsies and excised tumors, was prognostic in terms of DFS in cSCC but not in BSCC cases.

Tumour-stroma ratio is a valuable prognostic factor for oral tongue squamous cell carcinoma

OBJECTIVE

The objectives of this study were to estimate the prognostic value of the tumour-stroma ratio (TSR) and tumour budding (TB) in oral tongue squamous cell carcinoma (OTSCC) and to establish a reliable model to predict the outcome of OTSCC patients.

METHODS

A total of 103 patients surgically treated at our hospital were enrolled in this study. Chi-square tests, Kaplan-Meier analyses and Cox proportional hazards regression models were performed for statistical analysis.

RESULTS

Fifty-six patients were categorized as stroma-rich, and 47 patients were categorized as stroma-poor. Only pathological grade was associated with the TSR (p = 0.017). Kaplan-Meier analysis showed that stroma-rich, high-intensity budding and high risk groups were associated with worse prognosis. The Cox regression model showed that the TSR was an independent risk factor for OTSCC patients prognosis, and the high risk group was also related to poor prognosis (p < 0.05). TB was significantly associated with poor prognosis but was not an independent risk factor.

CONCLUSIONS

We found that patients in the stroma-rich group had a worse long-term prognosis. The TSR is an independent risk factor for OTSCC patients' outcome. In addition, a risk model that combined the TSR and TB proved to be valuable for predicting OTSCC patients' outcome.

Mesenchymal Stromal Cell-Based Targeted Therapy Pancreatic Cancer: Progress and Challenges

Pancreatic cancer is an aggressive malignancy with high mortality rates and poor prognoses. Despite rapid progress in the diagnosis and treatment of pancreatic cancer, the efficacy of current therapeutic strategies remains limited. Hence, better alternative therapeutic options for treating pancreatic cancer need to be urgently explored. Mesenchymal stromal cells (MSCs) have recently received much attention as a potential therapy for pancreatic cancer owing to their tumor-homing properties. However, the specific antitumor effect of MSCs is still controversial. To this end, we aimed to focus on the potential anti-cancer treatment prospects of the MSC-based approach and summarize current challenges in the clinical application of MSCs to treat pancreatic cancer.

Barriers and opportunities for gemcitabine in pancreatic cancer therapy

Pancreatic ductal adenocarcinoma (PDA) has become one of the leading causes of cancer-related deaths across the world. A lack of durable responses to standard-of-care chemotherapies renders its treatment particularly challenging and largely contributes to the devastating outcome. Gemcitabine, a pyrimidine antimetabolite, is a cornerstone in PDA treatment. Given the importance of gemcitabine in PDA therapy, extensive efforts are focusing on exploring mechanisms by which cancer cells evade gemcitabine cytotoxicity, but strategies to overcome them have not been translated into patient care. Here, we will introduce the standard treatment paradigm for patients with PDA, highlight mechanisms of gemcitabine action, elucidate gemcitabine resistance mechanisms, and discuss promising strategies to circumvent them.

Deep learning based tumor-stroma ratio scoring in colon cancer correlates with microscopic assessment

Background

The amount of stroma within the primary tumor is a prognostic parameter for colon cancer patients. This phenomenon can be assessed using the tumor-stroma ratio (TSR), which classifies tumors in stroma-low (≤50% stroma) and stroma-high (>50% stroma). Although the reproducibility for TSR determination is good, improvement might be expected from automation. The aim of this study was to investigate whether the scoring of the TSR in a semi- and fully automated method using deep learning algorithms is feasible.

Methods

A series of 75 colon cancer slides were selected from a trial series of the UNITED study. For the standard determination of the TSR, 3 observers scored the histological slides. Next, the slides were digitized, color normalized, and the stroma percentages were scored using semi- and fully automated deep learning algorithms. Correlations were determined using intraclass correlation coefficients (ICCs) and Spearman rank correlations.

Results

37 (49%) cases were classified as stroma-low and 38 (51%) as stroma-high by visual estimation. A high level of concordance between the 3 observers was reached, with ICCs of 0.91, 0.89, and 0.94 (all P < .001). Between visual and semi-automated assessment the ICC was 0.78 (95% CI 0.23-0.91, P-value 0.005), with a Spearman correlation of 0.88 (P < .001). Spearman correlation coefficients above 0.70 (N=3) were observed for visual estimation versus the fully automated scoring procedures.

Conclusion

Good correlations were observed between standard visual TSR determination and semi- and fully automated TSR scores. At this point, visual examination has the highest observer agreement, but semi-automated scoring could be helpful to support pathologists.

Features of tumor-microenvironment images predict targeted therapy survival benefit in patients with EGFR-mutant lung cancer

Tyrosine kinase inhibitors (TKIs) targeting epidermal growth factor receptor (EGFR) are effective for many patients with lung cancer with EGFR mutations. However, not all patients are responsive to EGFR TKIs, including even those harboring EGFR-sensitizing mutations. In this study, we quantified the cells and cellular interaction features of the tumor microenvironment (TME) using routine H&E-stained biopsy sections. These TME features were used to develop a prediction model for survival benefit from EGFR TKI therapy in patients with lung adenocarcinoma and EGFR-sensitizing mutations in the Lung Cancer Mutation Consortium 1 (LCMC1) and validated in an independent LCMC2 cohort. In the validation data set, EGFR TKI treatment prolonged survival in the predicted-to-benefit group but not in the predicted-not-to-benefit group. Among patients treated with EGFR TKIs, the predicted-to-benefit group had prolonged survival outcomes compared with the predicted not-to-benefit group. The EGFR TKI survival benefit positively correlated with tumor-tumor interaction image features and negatively correlated with tumor-stroma interaction. Moreover, the tumor-stroma interaction was associated with higher activation of the hepatocyte growth factor/MET-mediated PI3K/AKT signaling pathway and epithelial-mesenchymal transition process, supporting the hypothesis of fibroblast-involved resistance to EGFR TKI treatment.

Investigating the role of core needle biopsy in evaluating tumor-stroma ratio (TSR) of invasive breast cancer: a retrospective study

PURPOSE

Tumor-stroma ratio (TSR) of invasive breast carcinoma has gained attention in recent years due to its prognostic significance. Previous studies showed TSR is a potential biomarker for indicating the tumor response to neoadjuvant chemotherapy. However, it is not clear how well TSR evaluation in biopsy specimens might reflect the TSR in resection specimens. We conducted a study to investigate whether biopsy evaluation of TSR can be an alternative method.

METHOD

We collected cases with invasive breast carcinoma of no special type (IBC-NST) from University of Yamanashi hospital between 2011 and 2017 whose biopsy and resection specimens both had a pathologically diagnosis of IBC-NST (n = 146). We conceptualized a method for evaluating TSR in biopsy specimens within a preliminary cohort (n = 50). Within the studied cohort (n = 96), biopsy-based TSR (b-TSR) and resection-based TSR (r-TSR) were scored by two pathologists. We then evaluated our method's validity and performance by measuring interobserver variability between the two pathologists, Spearman's correlation between b-TSR and r-TSR, and the receiver operating characteristics (ROC) analysis for defining stroma-rich and stroma-poor tumors.

RESULTS

Intra-class coefficient between the two pathologists was 0.59. The correlation coefficients between b-TSR and r-TSR in the two pathologists were 0.45 and 0.37. The ROC areas under the curve were 0.7 and 0.67. By considering an r-TSR of < 50% as stroma-rich, the sensitivity and specificity of detecting stroma-rich tumors were 64.1% and 66.7%, respectively, when b-TSR was < 40%.

CONCLUSION

Our current b-TSR evaluation method can provide information about r-TSR and facilitate pre-treatment therapy follow-up.

Aberrant upregulation of CDK1 contributes to medroxyprogesterone acetate (MPA) resistance in cancer-associated fibroblasts of the endometrium

The response to medroxyprogesterone acetate (MPA) decreases as endometrial disease progresses from the benign to malignancy. In a mouse model, progesterone receptor (PR) expression in normal fibroblasts is accountable for the MPA's inhibitory effects in cancer cells. However, it is still unclear, if and how, fibroblasts from human tumors respond to MPA. In this study, three benign-associated fibroblasts (BAFs) and four cancer-associated fibroblasts (CAFs) were isolated from human benign and cancerous endometrial tissues, respectively, to examine MPA activation on PR signaling. PR-B protein expression were heterogeneously expressed in both CAFs and BAFs, despite a lower mRNA expression in the former. In a luciferase reporter assay, MPA treatment stimulated some PR DNA-binding activity in BAFs but not in CAFs. Yet, activation of PR target gene was generally more pronounced in MPA-treated CAFs compared to BAFs. Cyclin-dependent kinase 1 (CDK1) was exclusively upregulated by 10 nM MPA in CAFs (5.1-fold vs. 1.1-fold in BAFs, P < 0.05), leading to a higher CDK1 protein expression. Subsequently in a dose-response study, CAFs showed an average of ∼20% higher cell viability when compared to BAFs, indicative of drug resistance to MPA. MPA resistance was also observed in EC-CAFs co-culture, when MPA-treated cells showed greater tumor spheroid formation than in EC-BAFs co-culture (2-fold, P < 0.01). The increased cell viability observed in CAFs was reversed with mifepristone (RU486), a PR antagonist which suppressed MPA-induced CDK1 expression. This indicates that MPA-induced abnormal upregulation of CDK1 may contribute to the enhanced CAFs cell proliferation, suggesting a new mechanism of MPA resistance within endometrial cancer microenvironment.

Nonsurgical treatment options for basal cell carcinoma

ABSTRACT

Basal cell carcinoma (BCC) is the most common form of nonmelanoma skin cancer. Surgery, including Mohs micrographic surgery, is considered the gold standard for the management of BCC, yet some patients may be unable to undergo surgery. This article describes effective nonsurgical options for treating superficial BCCs as well as some nodular and infiltrative BCCs.

Artificial intelligence for quantifying immune infiltrates interacting with stroma in colorectal cancer

BACKGROUND

We proposed an artificial intelligence-based immune index, Deep-immune score, quantifying the infiltration of immune cells interacting with the tumor stroma in hematoxylin and eosin-stained whole-slide images of colorectal cancer.

METHODS

A total of 1010 colorectal cancer patients from three centers were enrolled in this retrospective study, divided into a primary (N = 544) and a validation cohort (N = 466). We proposed the Deep-immune score, which reflected both tumor stroma proportion and the infiltration of immune cells in the stroma region. We further analyzed the correlation between the score and CD3+ T cells density in the stroma region using immunohistochemistry-stained whole-slide images. Survival analysis was performed using the Cox proportional hazard model, and the endpoint of the event was the overall survival.

RESULT

Patients were classified into 4-level score groups (score 1-4). A high Deep-immune score was associated with a high level of CD3+ T cells infiltration in the stroma region. In the primary cohort, survival analysis showed a significant difference in 5-year survival rates between score 4 and score 1 groups: 87.4% vs. 58.2% (Hazard ratio for score 4 vs. score 1 0.27, 95% confidence interval 0.15-0.48, P < 0.001). Similar trends were observed in the validation cohort (89.8% vs. 67.0%; 0.31, 0.15-0.62, < 0.001). Stratified analysis showed that the Deep-immune score could distinguish high-risk and low-risk patients in stage II colorectal cancer (P = 0.018).

CONCLUSION

The proposed Deep-immune score quantified by artificial intelligence can reflect the immune status of patients with colorectal cancer and is associate with favorable survival. This digital pathology-based finding might advocate change in risk stratification and consequent precision medicine.

Artificial intelligence in pancreatic cancer

Pancreatic cancer is the deadliest disease, with a five-year overall survival rate of just 11%. The pancreatic cancer patients diagnosed with early screening have a median overall survival of nearly ten years, compared with 1.5 years for those not diagnosed with early screening. Therefore, early diagnosis and early treatment of pancreatic cancer are particularly critical. However, as a rare disease, the general screening cost of pancreatic cancer is high, the accuracy of existing tumor markers is not enough, and the efficacy of treatment methods is not exact. In terms of early diagnosis, artificial intelligence technology can quickly locate high-risk groups through medical images, pathological examination, biomarkers, and other aspects, then screening pancreatic cancer lesions early. At the same time, the artificial intelligence algorithm can also be used to predict the survival time, recurrence risk, metastasis, and therapy response which could affect the prognosis. In addition, artificial intelligence is widely used in pancreatic cancer health records, estimating medical imaging parameters, developing computer-aided diagnosis systems, etc. Advances in AI applications for pancreatic cancer will require a concerted effort among clinicians, basic scientists, statisticians, and engineers. Although it has some limitations, it will play an essential role in overcoming pancreatic cancer in the foreseeable future due to its mighty computing power.

Cancer-Associated Fibroblasts: The Origin, Biological Characteristics and Role in Cancer-A Glance on Colorectal Cancer

Simple Summary

Tumor microenvironment is a major contributor to tumor growth, metastasis and resistance to therapy. It consists of many cancer-associated fibroblasts (CAFs), which derive from different types of cells. CAFs detected in different tumor types are linked to poor prognosis, as in the case of colorectal cancer. Although their functions differ according to their subtype, their detection is not easy, and there are no established markers for such detection. They are possible targets for therapeutic treatment. Many trials are ongoing for their use as a prognostic factor and as a treatment target. More research remains to be carried out to establish their role in prognosis and treatment.

Abstract

The therapeutic approaches to cancer remain a considerable target for all scientists around the world. Although new cancer treatments are an everyday phenomenon, cancer still remains one of the leading mortality causes. Colorectal cancer (CRC) remains in this category, although patients with CRC may have better survival compared with other malignancies. Not only the tumor but also its environment, what we call the tumor microenvironment (TME), seem to contribute to cancer progression and resistance to therapy. TME consists of different molecules and cells. Cancer-associated fibroblasts are a major component. They arise from normal fibroblasts and other normal cells through various pathways. Their role seems to contribute to cancer promotion, participating in tumorigenesis, proliferation, growth, invasion, metastasis and resistance to treatment. Different markers, such as a-SMA, FAP, PDGFR-β, periostin, have been used for the detection of cancer-associated fibroblasts (CAFs). Their detection is important for two main reasons; research has shown that their existence is correlated with prognosis, and they are already under evaluation as a possible target for treatment. However, extensive research is warranted.

A cellular senescence-related gene prognostic index for biochemical recurrence and drug resistance in patients with prostate cancer

In this study, we aimed to establish a novel cellular senescence-related gene prognostic index (CSG PI) to predict biochemical recurrence (BCR) and drug resistance in patients with prostate cancer (PCa) undergoing radical radiotherapy or prostatectomy. We performed all analyses using R version 3.6.3 and its suitable packages. Cytoscape 3.8.2 was used to establish a network of transcription factors and competing endogenous RNAs. Three cellular senescence-related genes were used to establish the CSGPI. We observed that CSGPI was an independent risk factor for BCR in PCa patients (HR: 2.62; 95% CI: 1.55-4.44), consistent with the results of external validation (HR: 1.88; 95% CI: 1.12-3.14). The CSGPI had a moderate diagnostic effect on drug resistance (AUC: 0.812, 95% CI: 0.586-1.000). The lncRNA PART1 was significantly associated with BCR (HR: 0.46; 95% CI: 0.27-0.77), and might modulate the mRNA expression of definitive genes through interactions with 57 miRNAs. Gene set enrichment analysis indicated that CSGPI was closely related to ECM receptor interaction, focal adhesion, TGF beta signaling pathway, pathway in cancer, regulation of actin cytoskeleton, and so on. Immune checkpoint analysis showed that PDCD1LG2 and CD96 were significantly higher in the BCR group compared to non-BCR group, and patients with higher expression of CD96 were more prone to BCR than their counterparts (HR: 1.79; 95% CI: 1.06-3.03). In addition, the CSGPI score was significantly associated with the mRNA expression of HAVCR2, CD96, and CD47. Analysis of mismatch repair and methyltransferase genes showed that DNMT3B was more highly expressed in the BCR group and that patients with higher expression of DNMT3B experienced a higher risk of BCR (HR: 2.08; 95% CI: 1.23-3.52). We observed that M1 macrophage, CD8+ T cells, stromal score, immune score, and ESTIMATE score were higher in the BCR group. In contrast, tumor purity was less scored in the BCR group. Spearman analysis revealed a positive relationship between CSGPI and M1 macrophages, CD4+ T cells, dendritic cells, stromal score, immune score, and ESTIMATE score. In conclusion, we found that the CSGPI might serve as a biomarker to predict BCR and drug resistance in PCa patients. Moreover, CD96 and DNMT3B might be potential treatment targets, and immune evasion might contribute to the BCR process of PCa.