The proportion of tumor-stroma as a strong prognosticator for stage II and III colon cancer patients: validation in the VICTOR trial

The Glasgow Microenvironment Score: an exemplar of contemporary biomarker evolution in colorectal cancer

Colorectal cancer remains a leading cause of mortality worldwide. Significant variation in response to treatment and survival is evident among patients with similar stage disease. Molecular profiling has highlighted the heterogeneity of colorectal cancer but has had limited impact in daily clinical practice. Biomarkers with robust prognostic and therapeutic relevance are urgently required. Ideally, biomarkers would be derived from H&E sections used for routine pathological staging, have reliable sensitivity and specificity, and require minimal additional training. The biomarker targets would capture key pathological features with proven additive prognostic and clinical utility, such as the local inflammatory response and tumour microenvironment. The Glasgow Microenvironment Score (GMS), first described in 2014, combines assessment of peritumoural inflammation at the invasive margin with quantification of tumour stromal content. Using H&E sections, the Klintrup-Mäkinen (KM) grade is determined by qualitative morphological assessment of the peritumoural lymphocytic infiltrate at the invasive margin and tumour stroma percentage (TSP) calculated in a semi-quantitative manner as a percentage of stroma within the visible field. The resulting three prognostic categories have direct clinical relevance: GMS 0 denotes a tumour with a dense inflammatory infiltrate/high KM grade at the invasive margin and improved survival; GMS 1 represents weak inflammatory response and low TSP associated with intermediate survival; and GMS 2 tumours are typified by a weak inflammatory response, high TSP, and inferior survival. The prognostic capacity of the GMS has been widely validated while its potential to guide chemotherapy has been demonstrated in a large phase 3 trial cohort. Here, we detail its journey from conception through validation to clinical translation and outline the future for this promising and practical biomarker.

Combination of DNA ploidy, stroma, and nucleotyping predicting prognosis and tailoring adjuvant chemotherapy duration in stage III colon cancer

Introduction

DNA ploidy (P), stroma fraction (S), and nucleotyping (N) collectively known as PSN, have proven prognostic accuracy in stage II colorectal cancer (CRC). However, few studies have reported on the prognostic value of the PSN panel in stage III colon cancer patients receiving capecitabine and oxaliplatin adjuvant chemotherapy.

Objectives

This study aimed to validate PSN's prognostic impact on stage III colon cancer, identifying candidates for optimized adjuvant chemotherapy duration.

Design

A retrospective analysis was conducted on a cohort of stage III colon cancer patients from April 2008 to June 2020.

Methods

Postoperative pathological samples from stage III colon cancer patients who underwent radical surgery and postoperative adjuvant chemotherapy at Sun Yat-sen University Cancer Center were retrospectively collected. Automated digital imaging assessed PSN, categorizing risk groups. Kaplan-Meier, Cox regression, and time-dependent receiver operating characteristic analysis compared model validity.

Results

Significant differences in 5-year disease-free survival (DFS) and overall survival (OS) were noted among PSN-based low-, moderate-, and high-risk groups (DFS: 92.10% versus 83.62% versus 79.80%, p = 0.029; OS: 96.69% versus 93.99% versus 90.12%, p = 0.016). PSN emerged as an independent prognostic factor for DFS [hazard ratio (HR) = 1.409, 95% confidence interval (CI): 1.002-1.981, p = 0.049] and OS (HR = 1.720, 95% CI: 1.127-2.624, p = 0.012). The PSN model, incorporating perineural invasion and tumor location, displayed superior area under the curve for 5-year (0.692 versus 0.553, p = 0.020) and 10-year (0.694 versus 0.532, p = 0.006) DFS than TNM stage. In the PSN high-risk group, completing eight cycles of adjuvant chemotherapy significantly improved 5-year DFS and OS compared to four to seven cycles (DFS: 89.43% versus 71.52%, p = 0.026; OS: 96.77% versus 85.46%, p = 0.007).

Conclusion

The PSN panel effectively stratifies stage III colon cancer, aiding in optimized adjuvant chemotherapy duration determination.

Exploring prognostic values of DNA ploidy, stroma-tumor fraction and nucleotyping in stage II colon cancer patients

PURPOSE

To assess the prognostic value of three novel biomarkers, DNA ploidy, stroma-tumor fraction, and nucleotyping, seeking for more accurate stratification in stage II colon cancer.

METHODS

A total of 417 patients with complete follow up information were enrolled in this study and divided into three clinical risk groups. IHC was performed to examine MSI status. DNA ploidy, stroma and nucleotyping were estimated using automated digital imaging system. Kaplan-Meier survival curves, Cox proportional hazards regression models, and correlation analyses were carried out to process our data.

RESULTS

In the whole cohort of stage II colon cancer, nucleotyping and DNA ploidy were significant prognostic factors on OS in univariate analyses. The combination of nucleotyping and DNA ploidy signified superior OS and DFS. Difference was not significant between low-stroma and high-stroma patients. In multivariable analyses, nucleotyping and the combination of nucleotyping and DNA ploidy were proven the dominant contributory factors for OS. In the low-risk group, we found the combination of nucleotyping and DNA ploidy as the independent prognostic factor statistically significant in both univariate and multivariable, while in the high-risk group, the nucleotyping.

CONCLUSIONS

Our study has proven nucleotyping and the combination of DNA ploidy and nucleotyping as independent prognostic indicators, thus expanding the application of nucleotyping as a predictor from high risk stage II colon cancer to whole risks.

Thickness-Resolved Electrochemiluminescence Microscopy of Extracellular Matrix at Tumor Tissues for Rapid Cancer Diagnosis

The traditional recognition of extracellular matrix (ECM) at tissue sections relies on the time-consuming immunofluorescence that could not meet the demand of rapid diagnosis. Herein, we introduce a thickness-resolved electrochemiluminescence (ECL) microscopy to image thin-layer ECM at tissue sections for fast histopathological analysis. The unique surface-confined ECL mechanism enables to unveil the diversity and complexity of multiple tissue structures with varying thicknesses. Notably, the short lifetimes and the limited diffusion of electrogenerated coreactant radicals combined with their chemical reactivity result in a 2-fold increase in ECL intensity on ECM structures compared to the remaining tissue, enabling ECM visualization without specific labeling. The further quantitation of the ECM localization within tissue sections furnishes crucial insights into tumor progression and, more importantly, differentiates carcinoma and paracancerous tissues from patients in less than 30 min. Moreover, the reported electrochemistry-based microscopy is a dynamic approach allowing to investigate the transport, tortuosity, and trafficking properties through the tissues. This thickness-resolved recognition strategy not only opens new avenues for imaging complex samples but also holds promise for expediting tissue pathologic diagnosis, offering a more automated protocol with enhanced quantitative data compared to current intraoperative pathology methods.

Stroma AReactive Invasion Front Areas (SARIFA): a novel histopathologic biomarker in colorectal cancer patients and its association with the luminal tumour proportion

BACKGROUND

Stroma AReactive Invasion Front Areas (SARIFA) is a novel prognostic histopathologic biomarker measured at the invasive front in haematoxylin & eosin (H&E) stained colon and gastric cancer resection specimens. The aim of the current study was to validate the prognostic relevance of SARIFA-status in colorectal cancer (CRC) patients and investigate its association with the luminal proportion of tumour (PoT).

METHODS

We established the SARIFA-status in 164 CRC resection specimens. The relationship between SARIFA-status, clinicopathological characteristics, recurrence-free survival (RFS), cancer-specific survival (CSS), and PoT was investigated.

RESULTS

SARIFA-status was positive in 22.6% of all CRCs. SARIFA-positivity was related to higher pT, pN, pTNM stage and high grade of differentiation. SARIFA-positivity was associated with shorter RFS independent of known prognostic factors analysing all CRCs (RFS: hazard ratio (HR) 2.6, p = 0.032, CSS: HR 2.4, p = 0.05) and shorter RFS and CSS analysing only rectal cancers. SARIFA-positivity, which was measured at the invasive front, was associated with PoT-low (p = 0.009), e.g., higher stroma content, and lower vessel density (p = 0.0059) measured at the luminal tumour surface.

CONCLUSION

Here, we validated the relationship between SARIFA-status and prognosis in CRC patients and provided first evidence for a potential prognostic relevance in the subgroup of rectal cancer patients. Interestingly, CRCs with different SARIFA-status also showed histological differences measurable at the luminal tumour surface. Further studies to better understand the relationship between high luminal intratumoural stroma content and absence of a stroma reaction at the invasive front (SARIFA-positivity) are warranted and may inform future treatment decisions in CRC patients.

Impact of tumour stroma-immune interactions on survival prognosis and response to neoadjuvant chemotherapy in bladder cancer

BACKGROUND

The tumour stroma is associated with unfavourable prognosis in diverse solid tumours, but its prognostic and predictive value in bladder cancer (BCa) is unclear.

METHODS

In this multicentre, retrospective study, we included 830 patients with BCa from six independent cohorts. Differences in overall survival (OS) and cancer-specific survival (CSS) were investigated between high-tumour stroma ratio (TSR) and low-TSR groups. Multi-omics analyses, including RNA sequencing, immunohistochemistry, and single-cell RNA sequencing, were performed to study stroma-immune interactions. TSR prediction models were developed based on pelvic CT scans, and the best performing model was selected based on receiver operator characteristic analysis.

FINDINGS

Compared to low-TSR tumours, high-TSR tumours were significantly associated with worse OS (HR = 1.193, 95% CI: 1.046-1.361, P = 0.008) and CSS (HR = 1.337, 95% CI: 1.139-1.569, P < 0.001), and lower rate of pathological complete response (pCR) to neoadjuvant chemotherapy (NAC). High-TSR tumours exhibited higher infiltration of immunosuppressive cells, including Tregs and tumour-associated neutrophils, while low-TSR tumours exhibited higher infiltration of immune-activating cells such as CD8+ Teff and XCR1+ dendritic cells. The TSR prediction model was developed by combining the intra-tumour and tumour base radiomics features, and showed good performance to predict high-TSR, as indicted by area under the curve of 0.871 (95% CI: 0.821-0.921), 0.821 (95% CI: 0.731-0.911), and 0.801 (95% CI: 0.737-0.865) in the training, internal validation, and external validation cohorts, respectively. In patients with low predicted TSR, 92.3% (12/13) achieved pCR, while only 35.3% (6/17) of patients with high predicted TSR achieved pCR.

INTERPRETATION

The tumour stroma was found to be significantly associated with clinical outcomes in patients with BCa as a result of tumour stroma-immune interactions. The radiomics prediction model provided non-invasive evaluation of TSR and was able to predict pCR in patients receiving NAC for BCa.

FUNDING

This work was supported by National Natural Science Foundation of China (Grant No. 82373254 and 81961128027), Guangdong Provincial Natural Science Foundation (Grant No. 2023A1515010258), Science and Technology Planning Project of Guangdong Province (Grant No. 2023B1212060013). Science and Technology Program of Guangzhou (SL2022A04J01754), Sun Yat-Sen Memorial Hospital Clinical Research 5010 Program (Grant No. SYS-5010Z-202401).

Impact of STAT-signaling pathway on cancer-associated fibroblasts in colorectal cancer and its role in immunosuppression

Colorectal cancer (CRC) remains one of the most commonly diagnosed and deadliest types of cancer worldwide. CRC displays a desmoplastic reaction (DR) that has been inversely associated with poor prognosis; less DR is associated with a better prognosis. This reaction generates excessive connective tissue, in which cancer-associated fibroblasts (CAFs) are critical cells that form a part of the tumor microenvironment. CAFs are directly involved in tumorigenesis through different mechanisms. However, their role in immunosuppression in CRC is not well understood, and the precise role of signal transducers and activators of transcription (STATs) in mediating CAF activity in CRC remains unclear. Among the myriad chemical and biological factors that affect CAFs, different cytokines mediate their function by activating STAT signaling pathways. Thus, the harmful effects of CAFs in favoring tumor growth and invasion may be modulated using STAT inhibitors. Here, we analyze the impact of different STATs on CAF activity and their immunoregulatory role.

Histopathological tumour microenvironment score independently predicts outcome in primary operable colorectal cancer

Colorectal cancer (CRC) is a heterogenous malignancy and research is focused on identifying novel ways to subtype patients. In this study, a novel classification system, tumour microenvironment score (TMS), was devised based on Klintrup-Mäkinen grade (KMG), tumour stroma percentage (TSP), and tumour budding. TMS was performed using a haematoxylin and eosin (H&E)-stained section from retrospective CRC discovery and validation cohorts (n = 1,030, n = 787). TMS0 patients had high KMG, TMS1 were low for KMG, TSP, and budding, TMS2 were high for budding, or TSP and TMS3 were high for TSP and budding. Scores were assessed for association with survival and clinicopathological characteristics. Mutational landscaping and Templated Oligo-Sequencing (TempO-Seq) profiling were performed to establish differences in the underlying biology of TMS. TMS was independently prognostic in both cohorts (p < 0.001, p < 0.001), with TMS3 predictive of the shortest survival times. TMS3 was associated with adverse clinical features including sidedness, local and distant recurrence, higher T stage, higher N stage, and presence of margin involvement. Gene set enrichment analysis of TempO-Seq data showed higher expression of genes associated with hallmarks of cancer pathways including epithelial to mesenchymal transition (p < 0.001), IL2 STAT5 signalling (p = 0.007), and angiogenesis (p = 0.017) in TMS3. Additionally, enrichment of immunosuppressive immune signatures was associated with TMS3 classification. In conclusion, TMS represents a novel and clinically relevant method for subtyping CRC patients from a single H&E-stained tumour section.

The proportion of tumour stroma predicts response to treatment of immune checkpoint inhibitor in combination with chemotherapy in patients with stage IIIB-IV non-small cell lung cancer

AIMS

Immunotherapy has brought a new era to cancer treatment, yet we lack dependable predictors for its effectiveness. This study explores the predictive significance of intratumour stroma proportion (iTSP) for treatment success and prognosis in non-small cell lung cancer (NSCLC) patients undergoing treatment with immune check-point inhibitors (ICIs) together with chemotherapy.

METHODS AND RESULTS

We retrospectively collected data from patients with unresectable stage IIIB-IV NSCLC who were treated with first-line ICIs and chemotherapy. Each patient received a confirmed pathological diagnosis, and the pathologist evaluated the iTSP on haematoxylin and eosin (H&E)-stained sections of diagnostic tissue slides. Among the 102 H&E-stained biopsy samples, 61 (59.8%) were categorised as stroma-L (less than 50% iTSP), while 41 (40.2%) were classified as stroma-H (more than 50% iTSP). We observed that the stroma-L group exhibited a significantly better objective response rate (ORR) (72.1 versus 51.2%, P = 0.031) and deeper response depth (DpR) (-50.49 ± 28.79% versus -35.83 ± 29.91%, P = 0.015) compared to the stroma-H group. Furthermore, the stroma-L group showed longer median progression-free survival (PFS) (9.6 versus 6.0 months, P = 0.011) and overall survival (OS) (24.0 versus 12.2 months, P = 0.001) compared to the stroma-H group. Multivariate Cox proportional hazards regression analysis indicated that iTSP was a highly significant prognostic factor for both PFS [hazard ratio (HR) = 1.713; P = 0.030] and OS (HR = 2.225; P = 0.003).

CONCLUSION

Our findings indicate that a lower iTSP corresponds to improved clinical outcomes and greater DpR in individuals with stage IIIB-IV NSCLC treated with first-line ICIs and chemotherapy. The iTSP could potentially serve as a predictive biomarker for ICIs therapy response.

Construction and validation of a deep learning prognostic model based on digital pathology images of stage III colorectal cancer

BACKGROUND

TNM staging is the main reference standard for prognostic prediction of colorectal cancer (CRC), but the prognosis heterogeneity of patients with the same stage is still large. This study aimed to classify the tumor microenvironment of patients with stage III CRC and quantify the classified tumor tissues based on deep learning to explore the prognostic value of the developed tumor risk signature (TRS).

METHODS

A tissue classification model was developed to identify nine tissues (adipose, background, debris, lymphocytes, mucus, smooth muscle, normal mucosa, stroma, and tumor) in whole-slide images (WSIs) of stage III CRC patients. This model was used to extract tumor tissues from WSIs of 265 stage III CRC patients from The Cancer Genome Atlas and 70 stage III CRC patients from the Sixth Affiliated Hospital of Sun Yat-sen University. We used three different deep learning models for tumor feature extraction and applied a Cox model to establish the TRS. Survival analysis was conducted to explore the prognostic performance of TRS.

RESULTS

The tissue classification model achieved 94.4 % accuracy in identifying nine tissue types. The TRS showed a Harrell's concordance index of 0.736, 0.716, and 0.711 in the internal training, internal validation, and external validation sets. Survival analysis showed that TRS had significant predictive ability (hazard ratio: 3.632, p = 0.03) for prognostic prediction.

CONCLUSION

The TRS is an independent and significant prognostic factor for PFS of stage III CRC patients and it contributes to risk stratification of patients with different clinical stages.

Unselective Measurement of Tumor-to-Stroma Proportion in Colon Cancer at the Invasion Front-An Elusive Prognostic Factor: Original Patient Data and Review of the Literature

The tumor-to-stroma ratio is a highly debated prognostic factor in the management of several solid tumors and there is no universal agreement on its practicality. In our study, we proposed confirming or dismissing the hypothesis that a simple measurement of stroma quantity is an easy-to-use and strong prognostic tool. We have included 74 consecutive patients with colorectal cancer who underwent primary curative abdominal surgery. The tumors have been grouped into stroma-poor (stroma < 10%), medium-stroma (between 10 and 50%) and stroma-rich (over 50%). The proportion of tumor stroma ranged from 5% to 70% with a median of 25%. Very few, only 6.8% of patients, had stroma-rich tumors, 4% had stroma-poor tumors and 89.2% had tumors with a medium quantity of stroma. The proportion of stroma, at any cut-off, had no statistically significant influence on the disease-specific survival. This can be explained by the low proportion of stroma-rich tumors in our patient group and the inverse correlation between stroma proportion and tumor grade. The real-life proportion of stroma-rich tumors and the complex nature of the stroma-tumor interaction has to be further elucidated.

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

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

Predicting 5-year recurrence risk in colorectal cancer: development and validation of a histology-based deep learning approach

BACKGROUND

Accurate estimation of the long-term risk of recurrence in patients with non-metastatic colorectal cancer (CRC) is crucial for clinical management. Histology-based deep learning is expected to provide more abundant information for risk stratification.

METHODS

We developed and validated a weakly supervised deep-learning model for predicting 5-year relapse-free survival (RFS) to stratify patients with different risks based on histological images from three hospitals of 614 cases with non-metastatic CRC. A deep prognostic factor (DL-RRS) was established to stratify patients into high and low-risk group. The areas under the curve (AUCs) were calculated to evaluate the performances of models.

RESULTS

Our proposed model achieves the AUCs of 0.833 (95% CI: 0.736-0.905) and 0.715 (95% CI: 0.647-0.776) on validation cohort and external test cohort, respectively. The 5-year RFS rate was 45.7% for high DL-RRS patients, and 82.5% for low DL-RRS patients respectively in the external test cohort (HR: 3.89, 95% CI: 2.51-6.03, P < 0.001). Adjuvant chemotherapy was associated with improved RFS in Stage II patients with high DL-RRS (HR: 0.15, 95% CI: 0.06-0.38, P < 0.001).

CONCLUSIONS

DL-RRS has a good predictive performance of 5-year recurrence risk in CRC, and will better serve the clinical decision-making.

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.

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.

Diffusion MRI correlation with p16 status and prediction for tumor progression in locally advanced head and neck cancer

Purpose

To investigate p16 effects on diffusion image metrics and associations with tumor progression in patients with locally advanced head and neck cancers.

Methods

Diffusion images pretreatment and after 20 Gy (2wk) of RT were analyzed in patients with cT4/N3 p16+ oropharynx cancer (OPSCC) (N=51) and locoregionally advanced head and neck squamous cell carcinoma (LAHNSCC) (N=28), enrolled onto a prospective adaptive RT trial. Mean ADC values, subvolumes with ADC <1.2 um2/ms (TVLADC), and peak values of low (µL) and high (µH) components of ADC histograms in primary and total nodal gross tumor volumes were analyzed for prediction of freedom from local, distant, or any progression (FFLP, FFDP or FFLRDP) using multivariate Cox proportional-hazards model with clinical factors. P value with false discovery control <0.05 was considered as significant.

Results

With a mean follow up of 36 months, 18 of LAHNSCC patients and 16 of p16+ OPSCC patients had progression. After adjusting for p16, small µL and ADC values, and large TVLADC of primary tumors pre-RT were significantly associated with superior FFLRDP, FFLP and FFDP in the LAHNSCC (p<0.05), but no diffusion metrics were significant in p16+ oropharynx cancers. Post ad hoc analysis of the p16+ OPSCC only showed that large TVLADC of the total nodal burden pre-RT was significantly associated with inferior FFDP (p=0.05).

Conclusion

ADC metrics were associated with different progression patterns in the LAHNSCC and p16+ OPSCC, possibly explained by differences in cancer biology and morphology. A deep understanding of ADC metrics is warranted to establish imaging biomarkers for adaptive RT in HNSCC.

Deep Learning and Colon Cancer Interpretation: Rise of the Machine

The rapidly evolving development of artificial intelligence (AI) has spurred the development of numerous algorithms that augment information obtained from routine pathologic review of hematoxylin and eosin-stained slides. AI tools that predict prognosis and underlying molecular alterations have been the focus of much of the research to date. The results of these studies highlight the tremendous potential of AI to enhance our pathology reports by providing rapid predictions of key features that influence therapy and outcomes.

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 ).

Histopathology and levels of proteins in plasma associate with survival after colorectal cancer diagnosis

BACKGROUND

The TNM system is used to assess prognosis after colorectal cancer (CRC) diagnosis. Other prognostic factors reported include histopathological assessments of the tumour, tumour mutations and proteins in the blood. As some of these factors are strongly correlated, it is important to evaluate the independent effects they may have on survival.

METHODS

Tumour samples from 2162 CRC patients were visually assessed for amount of tumour stroma, severity of lymphocytic infiltrate at the tumour margins and the presence of lymphoid follicles. Somatic mutations in the tumour were assessed for 2134 individuals. Pre-surgical levels of 4963 plasma proteins were measured in 128 individuals. The associations between these features and prognosis were inspected by a Cox Proportional Hazards Model (CPH).

RESULTS

Levels of stroma, lymphocytic infiltration and presence of lymphoid follicles all associate with prognosis, along with high tumour mutation burden, high microsatellite instability and TP53 and BRAF mutations. The somatic mutations are correlated with the histopathology and none of the somatic mutations associate with survival in a multivariate analysis. Amount of stroma and lymphocytic infiltration associate with local invasion of tumours. Elevated levels of two plasma proteins, CA-125 and PPP1R1A, associate with a worse prognosis.

CONCLUSIONS

Tumour stroma and lymphocytic infiltration variables are strongly associated with prognosis of CRC and capture the prognostic effects of tumour mutation status. CA-125 and PPP1R1A may be useful prognostic biomarkers in CRC.

Going circular: history, present, and future of circRNAs in cancer

To date, thousands of highly abundant and conserved single-stranded RNA molecules shaped into ring structures (circRNAs) have been identified. CircRNAs are multifunctional molecules that have been shown to regulate gene expression transcriptionally and post-transcriptionally and exhibit distinct tissue- and development-specific expression patterns associated with a variety of normal and disease conditions, including cancer pathogenesis. Over the past years, due to their intrinsic stability and resistance to ribonucleases, particular attention has been drawn to their use as reliable diagnostic and prognostic biomarkers in cancer diagnosis, treatment, and prevention. However, there are some critical caveats to their utility in the clinic. Their circular shape limits their annotation and a complete functional elucidation is lacking. This makes their detection and biomedical application still challenging. Herein, we review the current knowledge of circRNA biogenesis and function, and of their involvement in tumorigenesis and potential utility in cancer-targeted therapy.

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

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

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

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

Expression Profile of Microenvironmental Factors in the Interface Zone of Colorectal Cancer: Histological-Stromal Biomarkers and Cancer Cell-Cancer-Associated Fibroblast-Related Proteins Combined for the Assessment of Tumor Progression

INTRODUCTION

The characterization of tumor microenvironment (TME) related factors and their impact on tumor progression have attracted much interest. We investigated cancer cells and cancer-associated fibroblasts (CAFs) to evaluate biomarkers that are associated with neoplastic progression, observing them in different interface zones of colorectal cancer.

METHODS

On 357 CRC tissue microarrays, using immunohistochemistry, we examined the associations of podoplanin and α-SMA expressed in cancer cells and CAFs and evaluated them in different areas: tumor core, invasive front, tumor budding, tumor-stroma ratio (TSR) scoring, and desmoplastic stroma.

RESULTS

CAFs expressing α-SMA were found in more than 90% of the cases. Podoplanin+ was detected in cancer cells and CAFs, with positivities of 38.6% and 70%, respectively. Higher α-SMA+ CAFs and podoplanin+ cancer cells were observed predominantly at the TSR score area: 94.3% and 64.3% of cases, respectively. The status of podoplanin in CAFs+ was higher in the desmoplastic area (71.6%). Stroma-high tumors showed increased expression of α-SMA and podoplanin in comparison with stroma-low tumors. The status of podoplanin in cancer cells was observed in association with lymphatic invasion and distant metastasis.

CONCLUSION

The substance of the CRC was composed predominantly of the surrounding stroma-α-SMA+ CAFs. Podoplanin expressed in the prognosticator zones was associated with unfavorable pathological features. The combination of histologic and protein-related biomarkers can result in a tool for the stratification of patients with CRC.

Node-negative colon cancer: histological, molecular, and stromal features predicting disease recurrence

BACKGROUND

Within the group of node-negative colon cancer patients, presumed to have a good prognosis, a significant percentage of patients develops cancer-recurrence. Current high-risk features prove inadequate to select these particular high-risk patients. In the process of tailor-made care and shared decision-making the need to identify these patients grows. In this study we investigate the value of adding molecular markers and the tumour-stroma ratio (TSR) to conventional histological tumour staging methods to improve the selection of high risk patients.

METHODS

We retrospectively analysed 201 patients diagnosed with TNM-stage I-II colon cancer and treated by complete oncological resection between November 1st 2002 and December 31st 2012 at the Jeroen Bosch Hospital. Conventional histological tumour staging, BRAF mutations, KRAS mutations, MSI status and TSR were determined. Differences between groups based on TSR and mutation status, in disease free survival were analysed using Cox-Regression analyses.

RESULTS

Poorly differentiated histology (p = 0.002), high-TSR (p = 0.033), BRAF-mutation (p = 0.008) and MSI (p = 0.011) were identified as significant risk factors for cancer recurrence. The risk of recurrence increased in the presence of both a BRAF-mutation and high-TSR compared to the absence of both factors or presence of only one factor (HR = 3.66 BRAF-mt/TSR-low (p = 0.006), HR 2.82 BRAF-wt/TSR-high (p = 0.015), HR = 4.39 BRAF-mt/TSR-high (p = 0.023)). This was also seen in tumours with MSI and high-TSR (HR = 2.46 MSS/TSR-high (p = 0.041), HR = 3.31 MSI/TSR-high (p = 0.045).

CONCLUSION

Judging by the higher HR for the combination of the prognostic factors TSR and BRAF compared to the HRs of these prognostic factors individually, the prognostication for disease free survival can be improved by determining both TSR and BRAF instead of BRAF alone, as is done in current daily practise. In this study MSI also shows additional value to TSR in the prognostication of disease free survival. Adopting TSR into daily diagnostics will be of additional value next to currently used molecular markers in risk stratification of patients with node negative colon cancer and is therefore advised.

Prognostic Value of Chromatin Structure Typing in Early-Stage Non-Small Cell Lung Cancer

(1) Background: Chromatin structure typing has been used for prognostic risk stratification among cancer survivors. This study aimed to ascertain the prognostic values of ploidy, nucleotyping, and tumor-stroma ratio (TSR) in predicting disease progression for patients with early-stage non-small cell lung cancer (NSCLC), and to explore whether patients with different nucleotyping profiles can benefit from adjuvant chemotherapy. (2) Methods: DNA ploidy, nucleotyping, and TSR were measured by chromatin structure typing analysis (Matrix Analyser, Room4, Kent, UK). Cox proportional hazard regression models were used to assess the relationships of DNA ploidy, nucleotyping, and TSR with a 5-year disease-free survival (DFS). (3) Results: among 154 early-stage NSCLC patients, 102 were non-diploid, 40 had chromatin heterogeneity, and 126 had a low stroma fraction, respectively. Univariable analysis suggested that non-diploidy was associated with a significantly lower 5-year DFS rate. After combining DNA ploidy and nucleotyping for risk stratification and adjusting for potential confounders, the DNA ploidy and nucleotyping (PN) high-risk group and PN medium-risk group had a 4- (95% CI: 1.497-8.754) and 3-fold (95% CI: 1.196-6.380) increase in the risk of disease progression or mortality within 5 years of follow-up, respectively, compared to the PN low-risk group. In PN high-risk patients, adjuvant therapy was associated with a significantly improved 5-year DFS (HR = 0.214, 95% CI: 0.048-0.957, p = 0.027). (4) Conclusions: the non-diploid DNA status and the combination of ploidy and nucleotyping can be useful prognostic indicators to predict long-term outcomes in early-stage NSCLC patients. Additionally, NSCLC patients with non-diploidy and chromatin homogenous status may benefit from adjuvant therapy.

Immunological and prognostic significance of tumour necrosis in colorectal cancer

BACKGROUND

Colorectal cancer (CRC) causes the second most cancer deaths worldwide, but the disease course varies according to tumour characteristics and immunological factors. Our objective was to examine the associations of tumour necrosis with tumour characteristics, immune cell infiltrates, serum cytokine concentrations, as well as prognosis in CRC.

METHODS

Three independent CRC cohorts, including 1413 patients, were analysed. Associations of the areal percentage of tumour necrosis with clinicopathologic parameters, tumour infiltrating immune cells, cytokine concentrations in systemic and mesenteric vein blood, and survival were examined.

RESULTS

Higher tumour necrosis percentage associated with shorter colorectal cancer-specific survival independent of tumour grade, T, N or M-class, mismatch repair status, BRAF status, and other possible confounding factors. In the largest cohort (N = 1100), the HR for high tumour necrosis percentage (≥40% vs. <3%) was 3.22 (95% CI 1.68-6.17, Ptrend < 0.0001). Tumour necrosis percentage positively correlated with peripheral serum levels of CXCL8, a proinflammatory chemokine, and negatively correlated with mesenteric serum levels of CXCL10 and mast cell densities in the invasive margin of the tumour.

CONCLUSIONS

Our results support the value of tumour necrosis as a prognostic factor in colorectal cancer. CXCL8 may have a role in the systemic effects of tumour necrosis.

Domain-specific transfer learning in the automated scoring of tumor-stroma ratio from histopathological images of colorectal cancer

Tumor-stroma ratio (TSR) is a prognostic factor for many types of solid tumors. In this study, we propose a method for automated estimation of TSR from histopathological images of colorectal cancer. The method is based on convolutional neural networks which were trained to classify colorectal cancer tissue in hematoxylin-eosin stained samples into three classes: stroma, tumor and other. The models were trained using a data set that consists of 1343 whole slide images. Three different training setups were applied with a transfer learning approach using domain-specific data i.e. an external colorectal cancer histopathological data set. The three most accurate models were chosen as a classifier, TSR values were predicted and the results were compared to a visual TSR estimation made by a pathologist. The results suggest that classification accuracy does not improve when domain-specific data are used in the pre-training of the convolutional neural network models in the task at hand. Classification accuracy for stroma, tumor and other reached 96.1% on an independent test set. Among the three classes the best model gained the highest accuracy (99.3%) for class tumor. When TSR was predicted with the best model, the correlation between the predicted values and values estimated by an experienced pathologist was 0.57. Further research is needed to study associations between computationally predicted TSR values and other clinicopathological factors of colorectal cancer and the overall survival of the patients.

Neural induction drives body axis formation during embryogenesis, but a neural induction-like process drives tumorigenesis in postnatal animals

Characterization of cancer cells and neural stem cells indicates that tumorigenicity and pluripotency are coupled cell properties determined by neural stemness, and tumorigenesis represents a process of progressive loss of original cell identity and gain of neural stemness. This reminds of a most fundamental process required for the development of the nervous system and body axis during embryogenesis, i.e., embryonic neural induction. Neural induction is that, in response to extracellular signals that are secreted by the Spemann-Mangold organizer in amphibians or the node in mammals and inhibit epidermal fate in ectoderm, the ectodermal cells lose their epidermal fate and assume the neural default fate and consequently, turn into neuroectodermal cells. They further differentiate into the nervous system and also some non-neural cells via interaction with adjacent tissues. Failure in neural induction leads to failure of embryogenesis, and ectopic neural induction due to ectopic organizer or node activity or activation of embryonic neural genes causes a formation of secondary body axis or a conjoined twin. During tumorigenesis, cells progressively lose their original cell identity and gain of neural stemness, and consequently, gain of tumorigenicity and pluripotency, due to various intra-/extracellular insults in cells of a postnatal animal. Tumorigenic cells can be induced to differentiation into normal cells and integrate into normal embryonic development within an embryo. However, they form tumors and cannot integrate into animal tissues/organs in a postnatal animal because of lack of embryonic inducing signals. Combination of studies of developmental and cancer biology indicates that neural induction drives embryogenesis in gastrulating embryos but a similar process drives tumorigenesis in a postnatal animal. Tumorigenicity is by nature the manifestation of aberrant occurrence of pluripotent state in a postnatal animal. Pluripotency and tumorigenicity are both but different manifestations of neural stemness in pre- and postnatal stages of animal life, respectively. Based on these findings, I discuss about some confusion in cancer research, propose to distinguish the causality and associations and discriminate causal and supporting factors involved in tumorigenesis, and suggest revisiting the focus of cancer research.

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

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

Spatially Resolved Transcriptomics Deconvolutes Prognostic Histological Subgroups in Patients with Colorectal Cancer and Synchronous Liver Metastases

Strong immune responses in primary colorectal cancer correspond with better patient survival following surgery compared with tumors with predominantly stromal microenvironments. However, biomarkers to identify patients with colorectal cancer liver metastases (CRLM) with good prognosis following surgery for oligometastatic disease remain elusive. The aim of this study was to determine the practical application of a simple histological assessment of immune cell infiltration and stromal content in predicting outcome following synchronous resection of primary colorectal cancer and CRLM and to interrogate the underlying functional biology that drives disease progression. Samples from patients undergoing synchronous resection of primary colorectal cancer and CRLM were evaluated in detail through histological assessment, panel genomic and bulk transcriptomic assessment, IHC, and GeoMx spatial transcriptomics (ST) analysis. High immune infiltration of metastases was associated with improved cancer-specific survival. Bulk transcriptomic analysis was confounded by stromal content, but ST demonstrated that the invasive edge of the metastases of long-term survivors was characterized by adaptive immune cell populations enriched for type II IFN signaling and MHC-class II antigen presentation. In contrast, patients with poor prognosis demonstrated increased abundance of regulatory T cells and neutrophils with enrichment of Notch and TGFβ signaling pathways at the metastatic tumor center. In summary, histological assessment can stratify outcomes in patients undergoing synchronous resection of CRLM, suggesting that it has potential as a prognostic biomarker. Furthermore, ST analysis has revealed significant intratumoral and interlesional heterogeneity and identified the underlying transcriptomic programs driving each phenotype.

SIGNIFICANCE

Spatial transcriptomics uncovers heterogeneity between patients, between matched lesions in the same patient, and within individual lesions and identifies drivers of metastatic progression in colorectal cancer with reactive and suppressed immune microenvironments.

Diagnostic performance of Ga-68 FAPI 04 PET/CT in colorectal malignancies

AIM

To evaluate the role of Ga-68 fibroblast activation protein inhibitor 04 PET/computed tomography (FAPI) in colorectal cancers (CRCs) in terms of diagnostic accuracy and impact on clinical management. FAPI is compared with FDG PET/CT and conventional imaging in staging, restaging, recurrence detection, and response evaluation of CRC.

METHODS

Twenty-nine consecutive patients of histopathologically confirmed primary or relapsed CRC were included in the study. Patients who underwent FAPI PET/CT along with either FDG PET/CT or conventional imaging were included. Primary lesions, recurrence sites, lymph nodes, and metastatic lesions were recorded on all the scans. Maximum standardized uptake value (SUVmax) was measured from both primary and metastatic lesions.

RESULTS

The sensitivity of FAPI in primary and recurrence detection is 100% compared to 88% for FDG/conventional imaging. The overall sensitivity of FAPI stands at 98% with accuracy at 95% whereas for FDG/conventional imaging the sensitivity and accuracy are 78% and 77%, respectively, with P  < 0.002. Significant difference was noted in the detection of peritoneal metastasis (96% vs. 66%).

CONCLUSION

FAPI PET/CT shows better sensitivity and accuracy in the evaluation of CRCs, especially in peritoneal disease compared to FDG PET/CT and conventional imaging. FAPI has the potential to replace FDG in CRCs.

Utility of Glasgow Microenvironment Score as a prognostic tool in colorectal carcinoma

Background

Colorectal carcinoma (CRC) is third most common malignancy in the world. The presence of Lymphocytes particularly at the invasive margin of the tumor have been associated with good immune response indicating better prognosis. The relative tumor stroma is also important in deciding the course of the disease. The Glasgow Microenvironment Score (GMS) comprises of assessment of tumor cell infiltrate using Klintrup-Makinen (KM) grade and tumor stroma percentage.

Aims

The aim of the present study is to evaluate the utility of GMS score in relation to parameters of adverse histopathological outcome in carcinoma colon that is grading, staging, LVI, PNI and nodal metastasis.

Setting and Design

Colectomy specimens received over 3 year period were subjected to microscopic evaluation for LVI, PNI, grade, stage & lymph node metastasis.

Materials and Methods

Lymphocytes at the deepest invasive margin of tumor were counted as per KM score in 5 HPF by two independent pathologists . Patients were classified as Low grade (0/1) or high grade (2/3) response. Tumor stroma percentage was calculated as stroma poor (<50%) and stroma rich (>/= 50 %). The GMS was scored by combining the two and scored 0, 1 and 2.

Statistics and Results

Total 37 patients with no prior therapy were included out of which 23 were males and 14 females. 15 patients (40.54%) had GMS of 0, 6 (16.21%) had GMS 1 and 16 (43.24%) had GMS 2. A high GMS was associated with LVI (P = 0.02), PNI (P = 0.01) lymph node metastasis (P = 0.003). However, no significant association was found between GMS with Grade (P = 0.98) and Stage (P = 0.36).

Conclusion

Low GMS was associated with good outcome and high GMS with poor outcome. This score can be used for risk stratification, can be of clinical utility and may be applied to pathological descriptions of CRC.

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.

Machine Learning Quantified Tumor-Stroma Ratio Is an Independent Prognosticator in Muscle-Invasive Bladder Cancer

Although the tumor-stroma ratio (TSR) has prognostic value in many cancers, the traditional semi-quantitative visual assessment method has inter-observer variability, making it impossible for clinical practice. We aimed to develop a machine learning (ML) algorithm for accurately quantifying TSR in hematoxylin-and-eosin (H&E)-stained whole slide images (WSI) and further investigate its prognostic effect in patients with muscle-invasive bladder cancer (MIBC). We used an optimal cell classifier previously built based on QuPath open-source software and ML algorithm for quantitative calculation of TSR. We retrospectively analyzed data from two independent cohorts to verify the prognostic significance of ML-based TSR in MIBC patients. WSIs from 133 MIBC patients were used as the discovery set to identify the optimal association of TSR with patient survival outcomes. Furthermore, we performed validation in an independent external cohort consisting of 261 MIBC patients. We demonstrated a significant prognostic association of ML-based TSR with survival outcomes in MIBC patients (p < 0.001 for all comparisons), with higher TSR associated with better prognosis. Uni- and multivariate Cox regression analyses showed that TSR was independently associated with overall survival (p < 0.001 for all analyses) after adjusting for clinicopathological factors including age, gender, and pathologic stage. TSR was found to be a strong prognostic factor that was not redundant with the existing staging system in different subgroup analyses (p < 0.05 for all analyses). Finally, the expression of six genes (DACH1, DEEND2A, NOTCH4, DTWD1, TAF6L, and MARCHF5) were significantly associated with TSR, revealing possible potential biological relevance. In conclusion, we developed an ML algorithm based on WSIs of MIBC patients to accurately quantify TSR and demonstrated its prognostic validity for MIBC patients in two independent cohorts. This objective quantitative method allows application in clinical practice while reducing the workload of pathologists. Thus, it might be of significant aid in promoting precise pathology services in MIBC.

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.

Ex vivo explant model of adenoma and colorectal cancer to explore mechanisms of action and patient response to cancer prevention therapies

Colorectal cancer (CRC) is the second leading cause of cancer death in the UK. Novel therapeutic prevention strategies to inhibit the development and progression of CRC would be invaluable. Potential contenders include low toxicity agents such as dietary-derived agents or repurposed drugs. However, in vitro and in vivo models used in drug development often do not take into account the heterogeneity of tumours or the tumour microenvironment. This limits translation to a clinical setting. Our objectives were to develop an ex vivo method utilizing CRC and adenoma patient-derived explants (PDEs) which facilitates screening of drugs, assessment of toxicity, and efficacy. Our aims were to use a multiplexed immunofluorescence approach to demonstrate the viability of colorectal tissue PDEs, and the ability to assess immune cell composition and interactions. Using clinically achievable concentrations of curcumin, we show a correlation between curcumin-induced tumour and stromal apoptosis (P < .001) in adenomas and cancers; higher stromal content is associated with poorer outcomes. B cell (CD20+ve) and T cell (CD3+ve) density of immune cells within tumour regions in control samples correlated with curcumin-induced tumour apoptosis (P < .001 and P < .05, respectively), suggesting curcumin-induced apoptosis is potentially predicted by baseline measures of immune cells. A decrease in distance between T cells (CD3+ve) and cytokeratin+ve cells was observed, indicating movement of T cells (CD3+ve) towards the tumour margin (P < .001); this change is consistent with an immune environment associated with improved outcomes. Concurrently, an increase in distance between T cells (CD3+ve) and B cells (CD20+ve) was detected following curcumin treatment (P < .001), which may result in a less immunosuppressive tumour milieu. The colorectal tissue PDE model offers significant potential for simultaneously assessing multiple biomarkers in response to drug exposure allowing a greater understanding of mechanisms of action and efficacy in relevant target tissues, that maintain both their structural integrity and immune cell compartments.

Quantitative Pathologic Analysis of Digitized Images of Colorectal Carcinoma Improves Prediction of Recurrence-Free Survival

BACKGROUND & AIMS

To examine whether quantitative pathologic analysis of digitized hematoxylin and eosin slides of colorectal carcinoma (CRC) correlates with clinicopathologic features, molecular alterations, and prognosis.

METHODS

A quantitative segmentation algorithm (QuantCRC) was applied to 6468 digitized hematoxylin and eosin slides of CRCs. Fifteen parameters were recorded from each image and tested for associations with clinicopathologic features and molecular alterations. A prognostic model was developed to predict recurrence-free survival using data from the internal cohort (n = 1928) and validated on an internal test (n = 483) and external cohort (n = 938).

RESULTS

There were significant differences in QuantCRC according to stage, histologic subtype, grade, venous/lymphatic/perineural invasion, tumor budding, CD8 immunohistochemistry, mismatch repair status, KRAS mutation, BRAF mutation, and CpG methylation. A prognostic model incorporating stage, mismatch repair, and QuantCRC resulted in a Harrell's concordance (c)-index of 0.714 (95% confidence interval [CI], 0.702-0.724) in the internal test and 0.744 (95% CI, 0.741-0.754) in the external cohort. Removing QuantCRC from the model reduced the c-index to 0.679 (95% CI, 0.673-0.694) in the external cohort. Prognostic risk groups were identified, which provided a hazard ratio of 2.24 (95% CI, 1.33-3.87, P = .004) for low vs high-risk stage III CRCs and 2.36 (95% CI, 1.07-5.20, P = .03) for low vs high-risk stage II CRCs, in the external cohort after adjusting for established risk factors. The predicted median 36-month recurrence rate for high-risk stage III CRCs was 32.7% vs 13.4% for low-risk stage III and 15.8% for high-risk stage II vs 5.4% for low-risk stage II CRCs.

CONCLUSIONS

QuantCRC provides a powerful adjunct to routine pathologic reporting of CRC. A prognostic model using QuantCRC improves prediction of recurrence-free survival.

Correlation of Immunological and Histopathological Features with Gene Expression-Based Classifiers in Colon Cancer Patients

The purpose of this study was to evaluate the association between four distinct histopathological features: (1) tumor infiltrating lymphocytes, (2) mucinous differentiation, (3) tumor-stroma ratio, plus (4) tumor budding and two gene expression-based classifiers—(1) consensus molecular subtypes (CMS) plus (2) colorectal cancer intrinsic subtypes (CRIS). All four histopathological features were retrospectively scored on hematoxylin and eosin sections of the most invasive part of the primary tumor in 218 stage II and III colon cancer patients from two independent cohorts (AMC-AJCC-90 and AC-ICAM). RNA-based CMS and CRIS assignments were independently obtained for all patients. Contingency tables were constructed and a χ2 test was used to test for statistical significance. Odds ratios with 95% confidence intervals were calculated. The presence of tumor infiltrating lymphocytes and a mucinous phenotype (>50% mucinous surface area) were strongly correlated with CMS1 (p < 0.001 and p = 0.008) and CRIS-A (p = 0.006 and p < 0.001). The presence of mucus (≥ 10%) was associated with CMS3: mucus was present in 64.1% of all CMS3 tumors (p < 0.001). Although a clear association between tumor-stroma ratio and CMS4 was established in this study (p = 0.006), still 32 out of 61 (52.5%) CMS4 tumors were scored as stroma-low, indicating that CMS4 tumors cannot be identified solely based on stromal content. Higher budding counts were seen in CMS4 and CRIS-B tumors (p = 0.045 and p = 0.046). No other associations of the measured parameters were seen for any of the other CRIS subtypes. Our analysis revealed clear associations between histopathologic features and CMS or CRIS subtypes. However, identification of distinct molecular subtypes solely based on histopathology proved to be infeasible. Combining both molecular and morphologic features could potentially improve patient stratification.

A prognostic six-gene expression risk-score derived from proteomic profiling of the metastatic colorectal cancer secretome

The necessity to accurately predict recurrence and clinical outcome in early stage colorectal cancer (CRC) is critical to identify those patients who may benefit from adjuvant chemotherapy. Here, we developed and validated a gene-based risk-score algorithm for patient stratification and personalised treatment in early stage disease based on alterations in the secretion of metastasis-related proteins. A quantitative label-free proteomic analysis of the secretome of highly and poorly metastatic CRC cell lines with different genetic backgrounds revealed 153 differentially secreted proteins (fold-change >5). These changes in the secretome were validated at the transcriptomic level. Starting from 119 up-regulated proteins, a six-gene/protein-based prognostic signature composed of IGFBP3, CD109, LTBP1, PSAP, BMP1, and NPC2 was identified after sequential discovery, training, and validation in four different cohorts. This signature was used to develop a risk-score algorithm, named SEC6, for patient stratification. SEC6 risk-score components showed higher expression in the poor prognosis CRC subtypes: consensus molecular subtype 4 (CMS4), CRIS-B, and stem-like. High expression of the signature was also associated with patients showing dMMR, CIMP⁺ status, and BRAF mutations. In addition, the SEC6 signature was associated with lower overall survival, progression-free interval, and disease-specific survival in stage II and III patients. SEC6-based risk stratification indicated that 5-FU treatment was beneficial for low-risk patients, whereas only aggressive treatments (FOLFOX and FOLFIRI) provided benefits to high-risk patients in stages II and III. In summary, this novel risk-score demonstrates the value of the secretome compartment as a reliable source for the retrieval of biomarkers with high prognostic and chemotherapy-predictive capacity, providing a potential new tool for tailoring decision-making in patient care.

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.

Vimentin and Ki-67 immunolabeling in canine gastric carcinomas and their prognostic value

This study evaluated the expression of vimentin and Ki-67 proliferative index (PI) by immunohistochemistry in 30 canine gastric carcinomas (GCs) and a possible association with clinical and pathological features and patient's survival time. Vimentin immunoreactivity was assessed in neoplastic cells (in primary lesions, emboli, and metastases) and tumor-associated stroma (TAS) of canine GCs. Ki-67 PI was quantified in the neoplastic epithelial component. Vimentin immunolabeling in neoplastic cells was found in 30% of the primary lesions, in 82% of the neoplastic emboli, and in 50% of the metastases; in TAS, it was observed in all cases. A mean of 16% of the TAS was immunolabeled for vimentin. High vimentin immunolabeling in the TAS (>16%) was detected in 40% of cases. The average value of Ki-67 PI was 50%, and 80% of the lesions had Ki-67 PI above 20%. Vimentin immunolabeling in neoplastic cells was more frequent in less-differentiated carcinomas (diffuse [29%] and indeterminate types [75%]) than well-differentiated carcinomas (intestinal type [0%], P = .049). No significant differences were observed in vimentin immunolabeling in the TAS or Ki-67 PI according to histological diagnosis, depth of invasion, presence of neoplastic emboli or metastases. However, vimentin immunolabeling in the TAS was positively correlated with Ki-67 PI (r = .394, P = .031). Furthermore, a moderate negative correlation was observed between Ki-67 PI and survival time (r = -0.540). Our results suggest that vimentin and Ki-67 PI have potential for providing prognostic information in cases of canine GCs.

Correlation between apparent diffusion coefficient and tumor-stroma ratio in hybrid 18F-FDG PET/MRI: preliminary results of a rectal cancer cohort study

Background

To explore possible correlations between the tumor-stroma ratio (TSR) and different imaging features of fluorine-18-fluorodeoxyglucose positron emission tomography/magnetic resonance imaging (¹⁸F-FDG PET/MRI) in untreated rectal cancer patients.

Methods

A patients with rectal cancer were included in this study. All participants were examined preoperatively with whole-body ¹⁸F-FDG PET/MRI. Two pathologists evaluated the TSR of tumors together. Apparent diffusion coefficient (ADC) values and PET-related parameters of the primary lesions were measured and compared between the stroma-high and stroma-low groups. Pearson's correlation or Spearman's rank correlation were used to evaluate the correlation between the ADC values, PET-related parameters, and pathological indices.

Results

Our results showed that in the untreated rectal cancer patients, the ADC mean values correlated with the TSR (r=0.327; P=0.007), and stroma-high (low TSR) rectal cancer corresponded to relatively lower ADC mean values (813.54±88.68 vs. 879.92±133.18; P=0.018). The ADC mean and ADC minimum (ADCmin) values were found to be negatively correlated with the pathological T stages (r=-0.384, P=0.001; r=-0.416, P=0.001, respectively) as well as the largest tumor diameters (r=-0.340, P=0.005; r=-0.314, P=0.010, respectively) of rectal cancer. In addition, the pathological T stages correlated with all PET-related metabolic parameters, including mean standard uptake value (SUV), maximum SUV (SUVmax), metabolic tumor volume (MTV), and total lesion glycolysis (TLG) (r=0.338, P=0.006; r=0.350, P=0.004; r=0.326, P=0.007; and r=0.472, P<0.001, respectively). Our results also identified associations between the ADCmin values and SUVmean, SUVmax, and TLG (r=-0.335, P=0.006; r=-0.343, P=0.005; and r=-0.343, P=0.005, respectively). However, there were no statistical correlations between the PET/MRI parameters and the immunohistochemical (IHC) results.

Conclusions

This study indicated that the intratumoral heterogeneity measured by PET/MRI may reflect characteristics of the tumor microenvironment. Hence, PET/MRI parameters might be helpful in predicting tumor aggressiveness and prognosis.

KIT promotes tumor stroma formation and counteracts tumor-suppressive TGFβ signaling in colorectal cancer

Expression profiling has identified four consensus molecular subtypes (CMS1-4) in colorectal cancer (CRC). The receptor tyrosine kinase KIT has been associated with the most aggressive subtype, CMS4. However, it is unclear whether, and how, KIT contributes to the aggressive features of CMS4 CRC. Here, we employed genome-editing technologies in patient-derived organoids (PDOs) to study KIT function in CRC in vitro and in vivo. CRISPR-Cas9-mediated deletion of the KIT gene caused a partial mesenchymal-to-epithelial phenotype switch and a strong reduction of intra-tumor stromal content. Vice versa, overexpression of KIT caused a partial epithelial-to-mesenchymal phenotype switch, a strong increase of intra-tumor stromal content, and high expression of TGFβ1. Surprisingly, the levels of phosphorylated SMAD2 were significantly lower in KIT-expressing versus KIT-deficient tumor cells. In vitro analyses showed that TGFβ signaling in PDOs limits their regenerative capacity. Overexpression of KIT prevented tumor-suppressive TGFβ signaling, while KIT deletion sensitized PDOs to TGFβ-mediated growth inhibition. Mechanistically, we found that KIT expression caused a strong reduction in the expression of SMAD2, a central mediator of canonical TGFβ signaling. We propose that KIT induces a pro-fibrotic tumor microenvironment by stimulating TGFβ expression, and protects the tumor cells from tumor-suppressive TGFβ signaling by inhibiting SMAD2 expression.

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

AIMS

In colorectal cancer (CRC) patients, a promising marker is tumor-stroma ratio (TSR). Quantification issues highlight the importance of precise assessment that might be solved by artificial intelligence (AI)-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 three distinct regions of interests (ROIs), like hotspot, invasive front and whole tumor. Furthermore, we compared the prognostic power of TSR with newly suggested carcinoma percentage (CP) and carcinoma-stroma percentage (CSP).

METHODS AND RESULTS

Slides of 185 stage I-IV CRC patients 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-hotspot_software: 2.005 (95% confidence interval (CI): 1.146-3.507), p=0.011, for TSR-hostpot_visual: 1.781 (CI: 1.060-2.992) p=0.029). 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.

CONCLUSIONS

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 convolutional neural network; however, it was still effective enough to deliver reliable prognostic information.

Proposal of an automated tumor-stromal ratio assessment algorithm and a nomogram for prognosis in early-stage invasive breast cancer

BACKGROUND

The tumor-stromal ratio (TSR) has been verified to be a prognostic factor in many solid tumors. In most studies, it was manually assessed on routinely stained H&E slides. This study aimed to assess the TSR using image analysis algorithms developed by the Qupath software, and integrate the TSR into a nomogram for prediction of the survival in invasive breast cancer (BC) patients.

METHODS

A modified TSR assessment algorithm based on the recognition of tumor and stroma tissues was developed using the Qupath software. The TSR of 234 invasive BC specimens in H&E-stained tissue microarrays (TMAs) were assessed with the algorithm and categorized as stroma-low or stroma-high. The consistency of TSR estimation between Qupath prediction and pathologist annotation was analyzed. Univariable and multivariable analyses were applied to select potential risk factors and a nomogram for predicting survival in invasive BC patients was constructed and validated. An extra TMA containing 110 specimens was obtained to validate the conclusion as an independent cohort.

RESULTS

In the discovery cohort, stroma-low and stroma-high were identified in 43.6% and 56.4% cases, respectively. Good concordance was observed between the pathologist annotated and Qupath predicted TSR. The Kaplan-Meier curve showed that stroma-high patients were associated with worse 5-DFS compared to stroma-low patients (p = 0.007). Multivariable analysis identified age, T stage, N status, histological grade, ER status, HER-2 gene, and TSR as potential risk predictors, which were included in the nomogram. The nomogram was well calibrated and showed a favorable predictive value for the recurrence of BC. Kaplan-Meier curves showed that the nomogram had a better risk stratification capability than the TNM staging system. In the external validation of the nomogram, the results were further validated.

CONCLUSIONS

Based on H&E-stained TMAs, this study successfully developed image analysis algorithms for TSR assessment and constructed a nomogram for predicting survival in invasive BC.

A high tumour-stroma ratio (TSR) in colon tumours and its metastatic lymph nodes predicts poor cancer-free survival and chemo resistance

PURPOSE

Despite known high-risk features, accurate identification of patients at high risk of cancer recurrence in colon cancer remains a challenge. As tumour stroma plays an important role in tumour invasion and metastasis, the easy, low-cost and highly reproducible tumour-stroma ratio (TSR) could be a valuable prognostic marker, which is also believed to predict chemo resistance.

METHODS

Two independent series of patients with colon cancer were selected. TSR was estimated by microscopic analysis of 4 µm haematoxylin and eosin (H&E) stained tissue sections of the primary tumour and the corresponding metastatic lymph nodes. Patients were categorized as TSR-low (≤ 50%) or TSR-high (> 50%). Differences in overall survival and cancer-free survival were analysed by Kaplan-Meier curves and cox-regression analyses. Analyses were conducted for TNM-stage I-II, TNM-stage III and patients with an indication for chemotherapy separately.

RESULTS

We found that high TSR was associated with poor cancer-free survival in TNM-stage I-II colon cancer in two independent series, independent of other known high-risk features. This association was also found in TNM-stage III tumours, with an additional prognostic value of TSR in lymph node metastasis to TSR in the primary tumour alone. In addition, high TSR was found to predict chemo resistance in patients receiving adjuvant chemotherapy after surgical resection of a TNM-stage II-III colon tumour.

CONCLUSION

In colon cancer, the TSR of both primary tumour and lymph node metastasis adds significant prognostic value to current pathologic and clinical features used for the identification of patients at high risk of cancer recurrence, and also predicts chemo resistance.

The Immune Microenvironment in Gastric Cancer: Prognostic Prediction

Although therapeutic methods have been developed, gastric cancer (GC) still leads to high rates of mortality and morbidity and is the fourth leading cause of cancer-associated death and the fifth most common cancer worldwide. To understand the factors associated with the prognostic prediction of GC and to discover efficient therapeutic targets, previous studies on tumour pathogenesis have mainly focused on the cancer cells themselves; in recent years, a large number of studies have shown that cancer invasion and metastasis are the results of coevolution between cancer cells and the microenvironment. It seems that studies on the tumour microenvironment could help in prognostic prediction and identify potential targets for treating GC. In this review, we mainly introduce the research progress for prognostic prediction and the immune microenvironment in GC in recent years, focusing on cancer-associated fibroblasts (CAFs), tumour-associated macrophages (TAMs), and tumour-infiltrating lymphocytes (TILs) in GC, and discuss the possibility of new therapeutic targets for GC.

Tumor Stroma Ratio and Its Significance in Locally Advanced Colorectal Cancer

Colorectal cancer is the third leading cause of cancer-related death, and its incidence is rising in the younger patient population. In the past decade, research has unveiled several processes (underlying tumorigenesis, many of which involve interactions between tumor cells and the surrounding tissue or tumor microenvironment (TME). Interactions between components of the TME are mediated at a sub-microscopic level. However, the endpoint of those interactions results in morphologic changes which can be readily assessed at microscopic examination of biopsy and resection specimens. Among these morphologic changes, alteration to the tumor stroma is a new, important determinant of colorectal cancer progression. Different methodologies to estimate the proportion of tumor stroma relative to tumor cells, or tumor stroma ratio (TSR), have been developed. Subsequent validation has supported the prognostic value, reproducibility and feasibility of TSR in various subgroups of colorectal cancer. In this manuscript, we review the literature surrounding TME in colorectal cancer, with a focus on tumor stroma ratio.

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.