Predictive potential of tumour-stroma ratio on benefit from adjuvant bevacizumab in high-risk stage II and stage III colon cancer

Tumor‑stroma ratio as a clinical prognostic factor in colorectal carcinoma: A meta‑analysis of 7,934 patients

The tumor-stroma ratio (TSR) has been regarded as an important factor associated with tumor metastasis, based on the 'seed and soil' theory, which may have guiding significance for the selection of chemotherapy regimens. Therefore, a high TSR may be a new risk factor for tumor recurrence in patients with stage II colorectal cancer (CRC). The present study aimed to evaluate the prognostic value of TSR in CRC, especially for the computer-calculated TSR. A comprehensive literature retrieval was performed using the PubMed, Web of Science, Embase and Cochrane Library databases to identify relevant studies published up to December 13, 2023. Pooled hazard ratios (HRs) with 95% confidence intervals (CIs) were calculated to estimate the prognostic value of the TSR in CRC. A total of 21 studies published between 2007 and 2023 were included in the present meta-analysis. The combined analysis demonstrated that a high TSR was significantly associated with worse overall survival (OS; HR=1.84; 95% CI, 1.44-2.34; P<0.001), disease-free survival (DFS; HR=1.85; 95% CI, 1.27-2.68; P<0.001), cancer-specific survival (CSS; H=1.97; 95% CI, 1.46-2.65; P<0.001) and recurrence free survival (RFS; HR=1.55; 95% CI, 1.25-1.92; P<0.001) in patients with CRC. Moreover, an elevated computer-calculated TSR was also associated with poor OS (HR=1.89; 95% CI, 1.48-2.40; P<0.001) and DFS (HR=1.85; 95% CI, 1.27-2.68; P<0.001). However, a high TSR was not associated with poor OS in patients with stage I CRC (HR=1.01; 95% CI, 0.48-2.14; P=0.97). In conclusion, the results of the present meta-analysis indicate that a high TSR is associated with poor OS, DFS, CSS and RFS in patients with CRC, especially for those with stage II-III. In addition, TSR calculated by computer using whole-slide images may also be an effective prognostic marker for OS and DFS in patients with CRC.

Self-supervised learning reveals clinically relevant histomorphological patterns for therapeutic strategies in colon cancer

Self-supervised learning (SSL) automates the extraction and interpretation of histopathology features on unannotated hematoxylin-eosin-stained whole slide images (WSIs). We train an SSL Barlow Twins encoder on 435 colon adenocarcinoma WSIs from The Cancer Genome Atlas to extract features from small image patches (tiles). Leiden community detection groups tiles into histomorphological phenotype clusters (HPCs). HPC reproducibility and predictive ability for overall survival are confirmed in an independent clinical trial (N = 1213 WSIs). This unbiased atlas results in 47 HPCs displaying unique and shared clinically significant histomorphological traits, highlighting tissue type, quantity, and architecture, especially in the context of tumor stroma. Through in-depth analyses of these HPCs, including immune landscape and gene set enrichment analyses, and associations to clinical outcomes, we shine light on the factors influencing survival and responses to treatments of standard adjuvant chemotherapy and experimental therapies. Further exploration of HPCs may unveil additional insights and aid decision-making and personalized treatments for colon cancer patients.

Mean Apparent Propagator MRI: Quantitative Assessment of Tumor-Stroma Ratio in Invasive Ductal Breast Carcinoma

Purpose To determine whether metrics from mean apparent propagator (MAP) MRI perform better than apparent diffusion coefficient (ADC) value in assessing the tumor-stroma ratio (TSR) status in breast carcinoma. Materials and Methods From August 2021 to October 2022, 271 participants were prospectively enrolled (ClinicalTrials.gov identifier: NCT05159323) and underwent breast diffusion spectral imaging and diffusion-weighted imaging. MAP MRI metrics and ADC were derived from the diffusion MRI data. All participants were divided into high-TSR (stromal component < 50%) and low-TSR (stromal component ≥ 50%) groups based on pathologic examination. Clinicopathologic characteristics were collected, and MRI findings were assessed. Logistic regression was used to determine the independent variables for distinguishing TSR status. The area under the receiver operating characteristic curve (AUC) and sensitivity, specificity, and accuracy were compared between the MAP MRI metrics, either alone or combined with clinicopathologic characteristics, and ADC, using the DeLong and McNemar test. Results A total of 181 female participants (mean age, 49 years ± 10 [SD]) were included. All diffusion MRI metrics differed between the high-TSR and low-TSR groups (P < .001 to P = .01). Radial non-Gaussianity from MAP MRI and lymphovascular invasion were significant independent variables for discriminating the two groups, with a higher AUC (0.81 [95% CI: 0.74, 0.87] vs 0.61 [95% CI: 0.53, 0.68], P < .001) and accuracy (138 of 181 [76%] vs 106 of 181 [59%], P < .001) than that of the ADC. Conclusion MAP MRI may serve as a better approach than conventional diffusion-weighted imaging in evaluating the TSR of breast carcinoma. Keywords: MR Diffusion-weighted Imaging, MR Imaging, Breast, Oncology ClinicalTrials.gov Identifier: NCT05159323 Supplemental material is available for this article. © RSNA, 2024.

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.

Self-Supervised Learning Reveals Clinically Relevant Histomorphological Patterns for Therapeutic Strategies in Colon Cancer

Self-supervised learning (SSL) automates the extraction and interpretation of histopathology features on unannotated hematoxylin-and-eosin-stained whole-slide images (WSIs). We trained an SSL Barlow Twins-encoder on 435 TCGA colon adenocarcinoma WSIs to extract features from small image patches. Leiden community detection then grouped tiles into histomorphological phenotype clusters (HPCs). HPC reproducibility and predictive ability for overall survival was confirmed in an independent clinical trial cohort (N=1213 WSIs). This unbiased atlas resulted in 47 HPCs displaying unique and sharing clinically significant histomorphological traits, highlighting tissue type, quantity, and architecture, especially in the context of tumor stroma. Through in-depth analysis of these HPCs, including immune landscape and gene set enrichment analysis, and association to clinical outcomes, we shed light on the factors influencing survival and responses to treatments like standard adjuvant chemotherapy and experimental therapies. Further exploration of HPCs may unveil new insights and aid decision-making and personalized treatments for colon cancer patients.

Prognostic prediction value of the clinical-radiomics tumour-stroma ratio in locally advanced rectal cancer

PURPOSE

To develop and validate a radiomics model based on high-resolution T2WI and a clinical-radiomics model for tumour-stroma ratio (TSR) evaluation with a gold standard of TSR evaluated by rectal specimens without therapeutic interference and further apply them in prognosis prediction of locally advanced rectal cancer (LARC) patients who received neoadjuvant chemoradiotherapy.

METHODS

A total of 178 patients (mean age: 59.35, range 20-85 years; 65 women and 113 men) with rectal cancer who received surgery alone from January 2016 to October 2020 were enrolled and randomly separated at a ratio of 7:3 into training and validation sets. A senior radiologist reviewed after 2 readers manually delineated the whole tumour in consensus on preoperative high-resolution T2WI in the training set. A total of 1046 features were then extracted, and recursive feature elimination embedded with leave-one-out cross validation was applied to select features, with which an MR-TSR evaluation model was built containing 6 filtered features via a support vector machine classifier trained by comparing patients' pathological TSR. Stepwise logistic regression was employed to integrate clinical factors with the radiomics model (Fusion-TSR) in the training set. Later, the MR-TSR and Fusion-TSR models were replicated in the validation set for diagnostic effectiveness evaluation. Subsequently, 243 patients (mean age: 53.74, range 23-74 years; 63 women and 180 men) with LARC from October 2012 to September 2017 who were treated with NCRT prior to surgery and underwent standard pretreatment rectal MR examination were enrolled. The MR-TSR and Fusion-TSR were applied, and the Kaplan-Meier method and log-rank test were used to compare the survival of patients with different MR-TSR and Fusion-TSR. Cox proportional hazards regression was used to calculate the hazard ratio (HR).

RESULTS

Both the MR-TSR and Fusion-TSR models were validated with favourable diagnostic power: the AUC of the MR-TSR was 0.77 (p = 0.01; accuracy = 69.8 %, sensitivity = 88.9 %, specificity = 65.9 %, PPV = 34.8 %, NPV = 96.7 %), while the AUC of the Fusion-TSR was 0.76 (p = 0.014; accuracy = 67.9 %, sensitivity = 88.9 %, specificity = 63.6 %, PPV = 33.3 %, NPV = 96.6 %), outperforming their effectiveness in the training set: the AUC of the MR-TSR was 0.65 (p = 0.035; accuracy = 66.4 %, sensitivity = 61.9 %, specificity = 67.3 %, PPV = 27.7 %, NPV = 90.0 %), while the AUC of the Fusion-TSR was 0.73 (p = 0.001; accuracy = 73.6 %, sensitivity = 71.4 %, specificity = 74.0 %, PPV = 35.73 %, NPV = 92.8 %). With further prognostic analysis, the MR-TSR was validated as a significant prognostic factor for DFS in LARC patients treated with NCRT (p = 0.020, HR = 1.662, 95 % CI = 1.077-2.565), while the Fusion-TSR was a significant prognostic factor for OS (p = 0.005, HR = 2.373, 95 % CI = 1.281-4.396).

CONCLUSIONS

We developed and validated a radiomics TSR and a clinical-radiomics TSR model and successfully applied them to better risk stratification for LARC patients receiving NCRT and for better decision making.

Value of the Tumor-Stroma Ratio and Structural Heterogeneity Measured by a Novel Semiautomatic Image Analysis Technique for Predicting Survival in Patients With Colon Cancer

BACKGROUND

The tumor-stroma ratio and intratumor stromal heterogeneity have been identified as prognostic factors for several carcinomas. Recent advancements in image analysis technologies and their application to medicine have enabled detailed analysis of clinical data beyond human cognition.

OBJECTIVE

This study aimed to investigate the tumor-stroma ratio and intratumor stromal heterogeneity measured using a novel objective and semiautomatic method with image analysis.

DESIGN

A retrospective cohort design.

SETTINGS

Single institution.

PATIENTS

This study included patients who underwent curative colectomy for colon cancer.

MAIN OUTCOME MEASURES

The survival analyses between tumor-stroma ratio or intratumor stromal heterogeneity high and low groups after colectomy were assessed in multivariate analyses.

RESULTS

Two hundred patients were divided into 2 groups based on the median tumor-stroma ratio and intratumor stromal heterogeneity values. The 5-year overall survival and relapse-free survival rates after colectomy significantly differed between the high and low tumor-stroma ratio or intratumor stromal heterogeneity groups. Multivariate analysis identified low tumor-stroma ratio (HR: 1.90, p = 0.03) and high intratumor stromal heterogeneity (HR: 2.44, p = 0.002) as independent poor prognostic factors for relapse-free survival. The tumor-stroma ratio and intratumor stromal heterogeneity correlated with the duration from curative surgery to recurrence. Furthermore, postoperative recurrence within 2 years was predicted with higher accuracy by using the tumor-stroma ratio or intratumor stromal heterogeneity than by using the pathological stage. In a validation cohort, interobserver agreement was assessed by 2 observers, and Cohen's κ coefficient for the tumor-stroma ratio (κ value: 0.70) and intratumor stromal heterogeneity (κ value: 0.60) revealed a substantial interobserver agreement.

LIMITATIONS

This study was limited by its retrospective, single-institution design.

CONCLUSIONS

Tumor-stroma ratio and intratumor stromal heterogeneity calculated using image analysis software have potential as imaging biomarkers for predicting the survival of patients with colon cancer after colectomy. See Video Abstract at http://links.lww.com/DCR/C114 .

VALOR DE LA PROPORCIN DE ESTROMA TUMORAL Y LA HETEROGENEIDAD ESTRUCTURAL MEDIDOS POR UNA NUEVA TCNICA DE ANLISIS DE IMGENES SEMIAUTOMTICA PARA PREDECIR LA SUPERVIVENCIA EN PACIENTES CON CNCER DE COLON

ANTECEDENTES:La proporción de estroma tumoral y la heterogeneidad del estroma intratumoral han sido identificados como factores pronósticos para varios tipos de carcinomas. Los avances recientes en cuanto a las tecnologías de análisis de imágenes y sus aplicaciones en la medicina, han permitido un análisis detallado de los datos clínicos más allá del conocimiento humano.OBJETIVO:Investigar la relación del estroma tumoral y la heterogeneidad del estroma intratumoral calculados mediante un nuevo método objetivo y semiautomático para el análisis de imágenes.DISEÑO:Diseño de cohorte retrospectivo.AJUSTES:Institución única.PACIENTES:Pacientes sometidos a colectomía curativa por cáncer de colon.PRINCIPALES MEDIDAS DE RESULTADO:Los análisis de supervivencia entre la relación del estroma tumoral o la heterogeneidad del estroma intratumoral entre los grupos con valores altos y bajos tras la colectomía, fueron evaluados en análisis multivariados.RESULTADOS:Fueron divididos 200 pacientes en dos grupos basados en la mediana de la proporción con respecto a los valores del estroma tumoral y la heterogeneidad del estroma intratumoral. Las tasas de supervivencia general a los 5 años y de supervivencia libre de recaídas después de la colectomía, difirieron significativamente entre los grupos con índice de estroma tumoral o heterogeneidad del estroma intratumoral altos y bajos. El análisis multivariante identificó una proporción de estroma tumoral baja (cociente de riesgos instantáneos: 1.90, p = 0.03) y una heterogeneidad estromal intratumoral alta (cociente de riesgos instantáneos: 2.44, p = 0.002) como factores independientes de mal pronóstico para la supervivencia libre de recaídas. La proporción de estroma tumoral y la heterogeneidad del estroma intratumoral se correlacionaron con la duración de la recurrencia desde la cirugía.Además, la recurrencia posoperatoria dentro de los 2 años se predijo con mayor precisión mediante el uso del índice de estroma tumoral o la heterogeneidad del estroma intratumoral que mediante el uso del estadio patológico. En una cohorte de validación, la concordancia interobservador fue evaluada por dos observadores, y el coeficiente Kappa de Cohen para la proporción de estroma tumoral y la heterogeneidad estromal intratumoral reveló una concordancia interobservador sustancial (valor Kappa: 0.70, 0.60, respectivamente).LIMITACIONES:Este estudio estuvo limitado por su diseño retrospectivo de una sola institución.CONCLUSIONES:La proporción del estroma tumoral y la heterogeneidad del estroma intratumoral calculadas mediante software de análisis de imágenes tienen potencial como biomarcadores de imagen para predecir la supervivencia de los pacientes con cáncer de colon tras la colectomía. Consulte Video Resumen en http://links.lww.com/DCR/C114 . (Traducción-Dr. Osvaldo Gauto ).

The tumour-associated stroma correlates with poor clinical outcomes and immunoevasive contexture in patients with upper tract urothelial carcinoma: results from a multicenter real-world study (TSU-01 Study)

BACKGROUND

In this real-world study, we aimed to elucidate the predictive value of tumour-associated stroma for clinical prognostic and therapeutic response in upper tract urothelial carcinoma (UTUC) by reviewing the clinicopathologic characteristics of 1015 UTUC patients through a nationwide multicenter analysis.

METHODS

The tumour-stroma ratio (TSR) was assessed based on tissue sections stained for hematoxylin and eosin (H&E), and patients were further stratified into stroma-high (>50% stroma) and stroma-low group (≤50% stroma). Kaplan-Meier curve and Cox regression hazard analysis were conducted to assess the survival outcomes of UTUC patients. Bioinformatics analysis and immunostaining analysis were applied to portray the tumour microenvironment (TME).

RESULTS

Stroma-high UTUC was significantly associated with poorer survival outcomes and inferior chemotherapeutic responsiveness. Our established nomogram achieved a high prognostic accuracy in predicting overall survival and cancer-specific survival in both of the discovery cohort (area under the curve [AUC] 0.663 and 0.712) and the validation cohort (AUC 0.741 and 0.747). Moreover, stroma-high UTUC was correlated with immunoevasive TME accompanied by increased cancer-associated fibroblasts, tumour-associated macrophages and, conspicuously a cluster of highly exhausted CD8+ T cells.

CONCLUSION

Our results showed stroma-high UTUC was associated with an inferior prognosis and an immunoevasive TME with exhausted CD8+ T cells in UTUC patients. Our TSR-based nomogram could be used to refine prognosis and inform treatment decisions of patients with UTUC.

The Prognostic Impact of Tumor Border Configuration, Tumor Budding and Tumor Stroma Ratio in Colorectal Carcinoma

OBJECTIVE

Tumor border configuration, tumor budding and tumor stroma ratio are reliable histopathological parameters that play a central role in the invasion-metastasis cascade. This study aimed to investigate the prognostic impact of these parameters and a new combined score in colorectal cancer.

MATERIAL AND METHOD

A cohort of 103 colorectal cancer surgical specimens was retrospectively evaluated for tumor border configuration, tumor budding and tumor stroma ratio using H&E sections. A combined risk score was then constructed to divide cases into low risk-tumors and high risk-tumors.

RESULTS

Infiltrating tumor border, high tumor budding, low tumor stroma ratio and high combined risk score were associated with positive lymph node involvement, presence of metastasis, high tumor grade, lymphovascular invasion, poor overall survival and short recurrence-free survival. Infiltrating tumor border, high tumor budding and high combined risk score were associated with advanced T stage. High tumor budding, and low tumor stroma ratio were associated with perineural invasion. Infiltrating tumor border was associated with increased tumor size and conventional adenocarcinoma, high tumor budding and low tumor stroma ratio. Low tumor stroma ratio was associated with high tumor budding. On multivariate survival analysis, tumor stroma ratio was found to be an independent predictor for overall survival and recurrence-free survival.

CONCLUSION

Tumor border configuration, tumor budding, tumor stroma ratio and the newly constructed combined risk score are potential predictors of outcome in colorectal cancer patients, suggesting that their incorporation in the routine histopathological evaluation could be useful in determining the prognosis of colorectal cancer cases.

Digital image analysis provides robust tissue microenvironment-based prognosticators in patients with stage I-IV colorectal cancer

In patients with colorectal cancer (CRC), a promising marker is tumor-stroma ratio (TSR). Quantification issues highlight the importance of precise assessment that might be solved by artificial intelligence-based digital image analysis systems. Some alternatives have been offered so far, although these platforms are either proprietary developments or require additional programming skills. Our aim was to validate a user-friendly, commercially available software running in everyday computational environment to improve TSR assessment and also to compare the prognostic value of assessing TSR in 3 distinct regions of interests, like hotspot, invasive front, and whole tumor. Furthermore, we compared the prognostic power of TSR with the newly suggested carcinoma percentage (CP) and carcinoma-stroma percentage (CSP). Slides of 185 patients with stage I-IV CRC with clinical follow-up data were scanned and evaluated by a senior pathologist. A machine learning-based digital pathology software was trained to recognize tumoral and stromal compartments. The aforementioned parameters were evaluated in the hotspot, invasive front, and whole tumor area, both visually and by machine learning. Patients were classified based on TSR, CP, and CSP values. On multivariate analysis, TSR-hotspot was found to be an independent prognostic factor of overall survival (hazard ratio for TSR-hotspotsoftware: 2.005 [95% confidence interval (CI): 1.146-3.507], P = .011, for TSR-hotspotvisual: 1.781 [CI: 1.060-2.992], P = .029). Also, TSR was an independent predictor for distant metastasis and local relapse in most settings. Generally, software performance was comparable to visual evaluation and delivered reliable prognostication in more settings also with CP and CSP values. This study presents that software-assisted evaluation is a robust prognosticator. Our approach used a less sophisticated and thus easily accessible software without the aid of a convolutional neural network; however, it was still effective enough to deliver reliable prognostic information.

Characteristics of tumour stroma in regional lymph node metastases in colorectal cancer patients: a theoretical framework for future diagnostic imaging with FAPI PET/CT

Purpose

The recently developed fibroblast activation protein inhibitor (FAPI) tracer for PET/CT, binding tumour-stromal cancer-associated fibroblasts, is a promising tool for detection of positive lymph nodes. This study provides an overview of features, including sizes and tumour-stromal content, of lymph nodes and their respective lymph node metastases (LNM) in colorectal cancer (CRC), since literature lacks on whether LNMs contain sufficient stroma to potentially allow FAPI-based tumour detection.

Methods

Haematoxylin and eosin-stained tissue slides from 73 stage III colon cancer patients were included. Diameters and areas of all lymph nodes and their LNMs were assessed, the amount of stroma by measuring the stromal compartment area, the conventional and total tumour-stroma ratios (TSR-c and TSR-t, respectively), as well as correlations between these parameters. Also, subgroup analysis using a minimal diameter cut off of 5.0 mm was performed.

Results

In total, 126 lymph nodes were analysed. Although positive correlations were observed between node and LNM for diameter and area (r = 0.852, p < 0.001 and r = 0.960, p < 0.001, respectively), and also between the LNM stromal compartment area and nodal diameter (r = 0.612, p < 0.001), nodal area (r = 0.747, p < 0.001) and LNM area (r = 0.746, p < 0.001), novel insight was that nearly all (98%) LNMs contained stroma, with median TSR-c scores of 35% (IQR 20–60%) and TSR-t of 20% (IQR 10–30%). Moreover, a total of 32 (25%) positive lymph nodes had a diameter of < 5.0 mm.

Conclusion

In LNMs, stroma is abundantly present, independent of size, suggesting a role for FAPI PET/CT in improved lymph node detection in CRC.

Serum-based measurements of stromal activation through ADAM12 associate with poor prognosis in colorectal cancer

Background

Recently it has been recognized that stromal markers could be used as a clinically relevant biomarker for therapy response and prognosis. Here, we report on a serum marker for stromal activation, A Disintegrin and Metalloprotease 12 (ADAM12) in colorectal cancer (CRC).

Methods

Using gene expression databases we investigated ADAM12 expression in CRC and delineated the source of ADAM12 expression. The clinical value of ADAM12 was retrospectively assessed in the CAIRO2 trial in metastatic CRC with 235 patients (31% of total cohort), and an independent rectal cancer cohort (n = 20).

Results

ADAM12 is expressed by activated CRC associated fibroblasts. In the CAIRO2 trial cohort, ADAM12 serum levels were prognostic (ADAM12 low versus ADAM12 high; median OS 25.3 vs. 17.1 months, HR 1.48 [95% CI 1.11–1.96], P = 0.007). The prognostic potential was specifically high for metastatic rectal cancer (HR 1.78 [95% CI 1.06–3.00], P = 0.030) and mesenchymal subtype tumors (HR 2.12 [95% CI 1.25–3.60], P = 0.004). ADAM12 also showed potential for predicting recurrence in an exploratory analysis of non-metastatic rectal cancers.

Conclusions

Here we describe a non-invasive marker for activated stroma in CRC which associates with poor outcome, especially for primary cancers located in the rectum.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12885-022-09436-0.

Tumor budding and fibrotic focus-proposed grading system for tumor budding in invasive carcinoma no special type of the breast

Tumor budding grade is a very useful histological prognostic indicator for colorectal cancer patients. Recently, it has been also reported as a significant prognostic indicator in invasive breast carcinoma patients. Our group and others have previously reported that the presence of a fibrotic focus in the tumor is a very useful histological finding for accurately predicting the prognosis in patients with invasive carcinoma of no special type (ICNST) of the breast. The purpose of the present study was to investigate whether a grading system incorporating tumor budding in a fibrotic focus is superior to the conventional grading system for tumor budding to accurately predict outcomes in patients with ICNST. According to our new grading system, we classified the tumors into grade I (164 cases), grade II (581 cases), and grade III (110 cases), and the results clearly demonstrated the significant superiority of the new grading system over that of conventional tumor budding alone for accurately predicting outcomes in patients with ICNST. Our findings strongly suggest that tumor cells and tumor-stromal cells interaction play very important roles in tumor progression rather than tumor cells alone.

Validation analysis of the novel imaging-based prognostic radiomic signature in patients undergoing primary surgery for advanced high-grade serous ovarian cancer (HGSOC)

BACKGROUND

Predictive models based on radiomics features are novel, highly promising approaches for gynaecological oncology. Here, we wish to assess the prognostic value of the newly discovered Radiomic Prognostic Vector (RPV) in an independent cohort of high-grade serous ovarian cancer (HGSOC) patients, treated within a Centre of Excellence, thus avoiding any bias in treatment quality.

METHODS

RPV was calculated using standardised algorithms following segmentation of routine preoperative imaging of patients (n = 323) who underwent upfront debulking surgery (01/2011-07/2018). RPV was correlated with operability, survival and adjusted for well-established prognostic factors (age, postoperative residual disease, stage), and compared to previous validation models.

RESULTS

The distribution of low, medium and high RPV scores was 54.2% (n = 175), 33.4% (n = 108) and 12.4% (n = 40) across the cohort, respectively. High RPV scores independently associated with significantly worse progression-free survival (PFS) (HR = 1.69; 95% CI:1.06-2.71; P = 0.038), even after adjusting for stage, age, performance status and residual disease. Moreover, lower RPV was significantly associated with total macroscopic tumour clearance (OR = 2.02; 95% CI:1.56-2.62; P = 0.00647).

CONCLUSIONS

RPV was validated to independently identify those HGSOC patients who will not be operated tumour-free in an optimal setting, and those who will relapse early despite complete tumour clearance upfront. Further prospective, multicentre trials with a translational aspect are warranted for the incorporation of this radiomics approach into clinical routine.

Impact of Tumor-Stroma Ratio on the Prognosis of Colorectal Cancer: A Systematic Review

BACKGROUND

It is critical to develop a reliable and cost-effective prognostic tool for colorectal cancer (CRC) stratification and treatment optimization. Tumor-stroma ratio (TSR) may be a promising indicator of poor prognosis in CRC patients. As a result, we conducted a systematic review on the predictive value of TSR in CRC.

METHODS

This study was carried out according to Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) 2020 guideline. An electronic search was completed using commonly used databases PubMed, CENTRAL, Cochrane Central Register of Controlled Trials, and Google scholar till the last search up to May 30, 2021. STATA version 13 was used to analyze the data.

RESULTS

A total of 13 studies [(12 for disease-free survival (DFS) and nine studies for overall survival (OS)] involving 4,857 patients met the inclusion criteria for the systematic review in the present study. In individuals with stage II CRC, stage III CRC, or mixed stage CRC, we observed a significantly higher pooled hazard ratio (HR) in those with a low TSR/greater stromal content (HR, 1.54; 95% CI: 1.20 to 1.88), (HR, 1.90; 95% CI: 1.35 to 2.45), and (HR, 1.70; 95% CI: 1.45 to 1.95), respectively, for predicting DFS. We found that a low TSR ratio had a statistically significant predictive relevance for stage II (HR, 1.43; 95% CI: 1.09 to 1.77) and mixed stages of CRC (HR, 1.65; 95% CI: 1.31 to 2.0) for outcome OS.

CONCLUSION

In patients with CRC, low TSR was found to be a prognostic factor for a worse prognosis (DFS and OS).

The value of the tumour-stroma ratio for predicting neoadjuvant chemoradiotherapy response in locally advanced rectal cancer: a case control study

BACKGROUND

The tumour-stroma ratio (TSR) is recognized as a practical prognostic factor in colorectal cancer. However, TSR assessment generally utilizes surgical specimens. This study aims to investigate whether the TSR evaluated from preoperative biopsy specimens by a semi-automatic quantification method can predict the response after neoadjuvant chemoradiotherapy (nCRT) of patients with locally advanced rectal cancer (LARC).

METHODS

A total of 248 consecutive patients diagnosed with LARC and treated with nCRT followed by resection were included. Haematoxylin and eosin (HE)-stained sections of biopsy specimens were collected, and the TSR was evaluated by a semi-automatic quantification method and was divided into three categories, using the cut-offs determined in the whole cohort to balance the proportion of patients in each category. The response to nCRT was evaluated on the primary tumour resection specimen by an expert pathologist using the four-tier tumour regression grade (TRG) system.

RESULTS

The TSR can discriminate patients that are major-responders (TRG 0-1) from patients that are non-responders (TRG 2-3). Patients were divided into stroma-low (33.5%), stroma-intermediate (33.9%), and stroma-high (32.7%) groups using 56.3 and 72.8% as the cutoffs. In the stroma-low group, 58 (69.9%) patients were major-responders, and only 39 (48.1%) patients were considered major-responders in the stroma-high group (P = 0.018). Multivariate analysis showed that the TSR was the only pre-treatment predictor of response to nCRT (adjusted odds ratio 0.40, 95% confidence interval 0.21-0.76, P = 0.002).

CONCLUSION

An elevated TSR in preoperative biopsy specimens is an independent predictor of nCRT response in LARC. This semi-automatic quantified TSR could be easily translated into routine pathologic assessment due to its reproducibility and reliability.

Prognostic Value of Tumor-Stroma Ratio in Rectal Cancer: A Systematic Review and Meta-analysis

Background

Tumor-stroma ratio (TSR) is a promising new prognostic predictor for patients with rectal cancer (RC). Although several studies focused on this pathologic feature, results from those studies were still inconsistent.

Methods

This research aimed to estimate the prognostic values of TSR for RC. A search of PubMed, EMBASE, and Web of Science was carried out. A meta-analysis was performed on disease-free survival, cancer-specific survival, and overall survival in patients with RC.

Results

The literature search generated 1,072 possible studies, of which a total of 15 studies, involving a total of 5,408 patients, were eventually included in the meta-analysis. Thirteen of the 15 articles set the cutoff for the ratio of stroma at 50%, dividing patients into low-stroma and high-stroma groups. Low TSR (rich-stroma) was significantly associated with poorer survival outcome. (DFS: HR 1.54, 95% CI 1.32–1.79; OS: HR 1.52 95% CI 1.34–1.73; CSS: HR 2.05 95% CI 1.52–2.77).

Conclusion

Present data support TSR to be a risk predictor for poor prognosis in RC patients.

The prognostic value of tumor-stromal ratio combined with TNM staging system in esophagus squamous cell carcinoma

Background: Tumor stroma is a crucial component of the tumor environment that interacted with tumor cells and modulated tumor cell proliferation, immune evasion, and metastasis. Tumor-stromal ratio (TSR) has been confirmed as an influential independent prognostic factor for diverse types of cancer, but it was seldom discussed in esophagus squamous cell carcinoma (ESCC). Methods: In present study, pathological sections from the most invasive part of the ESCC of 270 patients were analyzed for their TSR by visual inspection and software. The TSR was combined with the TNM staging system to further explain its predictive value of prognosis. The 57 cases ESCC from TCGA database also were included as an independently validated cohort. Results: Our results indicated that TSR was a robust prognostic factor for ESCC patients. TSR by visual inspection was dependable to reflect the stroma percent of the tumor compared to software calculation. Compared with stroma-low groups, the risk of death increased by 153.1% for patients in the stroma-high group [HR=2.531 (95%CI 1.657-3.867), P<0.001]. The results of ROC analysis in two cohorts indicated that TSNM staging system had better resolving ability with the largest area under the curve [0.698 95%CI (0.635-0.760), 0.691 95%CI (0.555-0.807)], compare to TNM. The novel TSNM staging system revealed strong predictive performance (P<0.001). Conclusion: TSR was a reliable dependent indicator for ESCC prognosis. The TSNM staging system has a better discriminative ability than the conventional TNM staging system, especially for III stage patients.

Correlation of the tumour-stroma ratio with diffusion weighted MRI in rectal cancer

OBJECTIVE

This study evaluated the correlation between intratumoural stroma proportion, expressed as tumour-stroma ratio (TSR), and apparent diffusion coefficient (ADC) values in patients with rectal cancer.

METHODS

This multicentre retrospective study included all consecutive patients with rectal cancer, diagnostically confirmed by biopsy and MRI. The training cohort (LUMC, Netherlands) included 33 patients and the validation cohort (VHIO, Spain) 69 patients. Two observers measured the mean and minimum ADCs based on single-slice and whole-volume segmentations. The TSR was determined on diagnostic haematoxylin & eosin stained slides of rectal tumour biopsies. The correlation between TSR and ADC was assessed by Spearman correlation (r_s).

RESULTS

The ADC values between stroma-low and stroma-high tumours were not significantly different. Intra-class correlation (ICC) demonstrated a good level of agreement for the ADC measurements, ranging from 0.84-0.86 for single slice and 0.86-0.90 for the whole-volume protocol. No correlation was observed between the TSR and ADC values, with ADC_meanr_s= -0.162 (p= 0.38) and ADC_minr_s= 0.041 (p= 0.82) for the single-slice and r_s= -0.108 (p= 0.55) and r_s= 0.019 (p= 0.92) for the whole-volume measurements in the training cohort, respectively. Results from the validation cohort were consistent; ADC_meanr_s= -0.022 (p= 0.86) and ADC_minr_s = 0.049 (p= 0.69) for the single-slice and r_s= -0.064 (p= 0.59) and r_s= -0.063 (p= 0.61) for the whole-volume measurements.

CONCLUSIONS

Reproducibility of ADC values is good. Despite positive reports on the correlation between TSR and ADC values in other tumours, this could not be confirmed for rectal cancer.

Gastric cancer nodal tumour-stroma ratios influence prognosis

This study showed that nodal tumour-stroma ratio (NTSR) is an independent prognostic factor for overall and disease-free survival of patients with gastric cancer. Both relative stroma-rich primary tumour-stroma ratio (PTSR) and NTSR were independent negative prognostic factors for overall survival in gastric cancer. This study supports assessment of tumour-stroma ratio in the routine pathological diagnosis of gastric cancer. validated in node-positive disease.

Increased RAB31 Expression in Cancer-Associated Fibroblasts Promotes Colon Cancer Progression Through HGF-MET Signaling

RAB family proteins participate in the dynamic regulation of cellular membrane compartments and are dysregulated in a variety of tumor types, which may alter the biological properties of cancer cells such as proliferation, migration, and invasion. In our previous study, we found that Ras-related protein Rab-31 (RAB31) expression was increased in late-stage colorectal cancer (CRC). The role of RAB31 has never been investigated in CRC. In this study, we found that expression of RAB31 in the tumor stroma but not cancer cells of colon cancer predicted poor survival. RAB31 can be detected in primary cancer-associated fibroblasts (CAFs) and paired normal fibroblasts. Conditioned medium (CM) from RAB31 overexpressing CAFs significantly promoted migration of colon cancer cell lines in vitro and in vivo. This process may be mediated by paracrine action of hepatocyte growth factor (HGF), which was increased in the CM of RAB31-overexpressing CAFs. Blockade of HGF/MET signaling by drug inhibition, knockdown of mesenchymal to epithelial transition factor (MET) in RKO, or antibody neutralization of HGF abolished migration of RKO cells mediated by RAB31 expression in CAFs. We propose that in colon cancer, increased RAB31 expression in CAFs may contribute to tumor progression by regulating the secretion of HGF in the tumor stroma.

Value of intra-tumor heterogeneity evaluated by diffusion-weighted MRI for predicting pathological stages and therapeutic responses to chemoradiotherapy in lower rectal cancer

Aim: Diffusion-weighted MRI (DWI) has the potential to reveal intra-tumor structural heterogeneity consisting of stroma through an evaluation of uniformity on DWI. In present study, we examined the diagnostic value of intra-tumor heterogeneity evaluated by DWI in lower rectal cancer (LRC).

Patients and Methods: A total of 172 LRC patients underwent radical surgery between 2009 and 2017. T1 tumors and cases without pre-operative MRI were excluded. Twenty-nine primary resection cases (PR) and 37 pre-operative chemoradiotherapy followed by radical surgery cases (pCRT) were targeted. Intra-tumor heterogeneity on DWI was quantified using a specific formula (HSD). Structural heterogeneity was objectively quantified by an image analysis of resected specimens using a digital microscope (HSP). The relationships between HSD and HSP, pathological factors, and tumor regression grades (TRG) of pCRT were evaluated.

Results: The relationship between HSD and HSP was analyzed by a linear regression model in PR cases, revealing a positive correlation (R²=0.43). PR cases were divided into HSD-high and HSD-low according to the median. There were more pT3 or N(+) cases in HSD-high (p=0.038, 0.095). HSD before pCRT correlated with TRG (grade 1 versus 2/3) in pCRT cases (p=0.001). The diagnostic accuracy of HSD for predicting T and N stages and therapeutic grades was evaluated by cut-off values calculated using a ROC curve and revealed that each factor may be accurately diagnosed.

Conclusion: Intra-tumor heterogeneity on DWI corresponded with stromal pathological heterogeneity. It is useful for predicting T3 or deeper tumor invasion, pathological N(+), and the therapeutic effects of pCRT.

Stromal organization as predictive biomarker for the treatment of colon cancer with adjuvant bevacizumab; a post-hoc analysis of the AVANT trial

PURPOSE

Intra-tumoral stroma has become increasingly important in understanding tumor biology, tumor progression and clinical outcome. The amount itself, quantified as the tumor-stroma ratio (TSR), has proven to be prognostic in stage I-III colon cancer. Also, alterations in stromal organization have been found to provide prognostic and predictive information in certain cancers. Here, we evaluated the predictive value of stromal organization in high-risk stage II and III colon cancer with respect to adjuvant bevacizumab and chemotherapy.

METHODS

In a post-hoc analysis, stromal organization was microscopically determined in hematoxylin and eosin-stained primary tumor tissue samples of 1226 patients enrolled in the AVANT trial.

RESULTS

We found that patients with tumors with a disorganized stroma showed different survival rates after the addition of bevacizumab compared to standard oxaliplatin-based chemotherapy regimens. However, overall this difference was not significant with a HR of 0.94 (95% CI 0.57-1.55; p = 0.80) for disease-free survival (DFS) and 1.01 (95% CI 0.51-1.99; p = 0.99) for overall survival (OS). Subgroup analysis, however, revealed that stromal organization combined with TSR allowed the identification of stroma-high patients with absolute cumulative survival benefits up to 15% when bevacizumab was added to oxaliplatin-based chemotherapy regimens.

CONCLUSIONS

In high-risk stage II and stage III colon cancer, we found that subgroup analysis of the combined parameters stromal organization and TSR allows for the identification of patients with absolute cumulative DFS and OS benefits of up to 15%, when adding bevacizumab to the currently recommended oxaliplatin-based chemotherapy. Stromal organization itself does, however, not serve as an independent prognostic or predictive parameter.