The relationship between tumour stroma percentage, the tumour microenvironment and survival in patients with primary operable colorectal cancer

Concomitant expression patterns of CDX2 and SATB2 as prognostic factors in stage III colorectal cancers

CDX2 and SATB2 are often used as biomarkers for identification of colorectal origin in primary or metastatic adenocarcinomas. Loss of CDX2 or SATB2 expression has been associated with poor prognosis in patients with colorectal cancer (CRC). However, little is known regarding clinicopathological features, including prognosis, of CRCs with concomitant loss of CDX2 and SATB2. A total of 431 stage III CRCs were analyzed for their expression status in CDX2 and SATB2 using tissue microarray-based immunohistochemistry and expression status was correlated with clinicopathological variables, molecular alterations, and survival. CDX2-negative (CDX2-) CRCs and SATB2-negative (SATB2-) CRCs were found in 8.1 % and 17.2 % of CRCs, respectively, whereas both CDX2-negative and SATB2-negative (CDX2-/SATB2-) CRCs comprised 3.2 % of the CRCs. On survival analysis, neither CDX2-/SATB2+ nor CDX2+/SABT2- CRCs but CDX2-/SATB2- CRCs were associated with poor prognosis. CDX2-/SATB2- CRCs showed significant associations with tumor subsite of right colon, poor differentiation, decreased expression of CK20, aberrant expression of CK7, CIMP-high, MSI-high, and BRAF mutation. In summary, our results suggest that concomitant loss of CDX2 and SATB2 is a prognostic biomarker but isolated loss of CDX2 or SATB2 is not a prognostic biomarker for stage III CRCs.

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.

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.

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.

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.

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.

Natural Product Quercetin-3-methyl ether Promotes Colorectal Cancer Cell Apoptosis by Downregulating Intracellular Polyamine Signaling

Dysregulation of cellular metabolism is a key marker of cancer, and it is suggested that metabolism should be considered as a targeted weakness of colorectal cancer. Increased polyamine metabolism is a common metabolic change in tumors. Thus, targeting polyamine metabolism for anticancer therapy, particularly polyamine blockade therapy, has gradually become a hot topic. Quercetin-3-methyl ether is a natural compound existed in various plants with diverse biological activities like antioxidant and antiaging. Here, we reported that Quercetin-3-methyl ether inhibits colorectal cancer cell viability, and promotes apoptosis in a dose-dependent and time-dependent manner. Intriguingly, the polyamine levels, including spermidine and spermine, in colorectal cancer cells were reduced upon treatment of Quercetin-3-methyl ether. This is likely resulted from the downregulation of SMOX, a key enzyme in polyamine metabolism that catalyzes the oxidation of spermine to spermidine. These findings suggest Quercetin-3-methyl ether decreases cellular polyamine level by suppressing SMOX expression, thereby inducing colorectal cancer cell apoptosis. Our results also reveal a correlation between the anti-tumor activity of Quercetin-3-methyl ether and the polyamine metabolism modulation, which may provide new insights into a better understanding of the pharmacological activity of Quercetin-3-methyl ether and how it reprograms cellular polyamine metabolism.

JAK/STAT3 represents a therapeutic target for colorectal cancer patients with stromal-rich tumors

Colorectal cancer (CRC) is a heterogenous malignancy underpinned by dysregulation of cellular signaling pathways. Previous literature has implicated aberrant JAK/STAT3 signal transduction in the development and progression of solid tumors. In this study we investigate the effectiveness of inhibiting JAK/STAT3 in diverse CRC models, establish in which contexts high pathway expression is prognostic and perform in depth analysis underlying phenotypes. In this study we investigated the use of JAK inhibitors for anti-cancer activity in CRC cell lines, mouse model organoids and patient-derived organoids. Immunohistochemical staining of the TransSCOT clinical trial cohort, and 2 independent large retrospective CRC patient cohorts was performed to assess the prognostic value of JAK/STAT3 expression. We performed mutational profiling, bulk RNASeq and NanoString GeoMx® spatial transcriptomics to unravel the underlying biology of aberrant signaling. Inhibition of signal transduction with JAK1/2 but not JAK2/3 inhibitors reduced cell viability in CRC cell lines, mouse, and patient derived organoids (PDOs). In PDOs, reduced Ki67 expression was observed post-treatment. A highly significant association between high JAK/STAT3 expression within tumor cells and reduced cancer-specific survival in patients with high stromal invasion (TSPhigh) was identified across 3 independent CRC patient cohorts, including the TrasnSCOT clinical trial cohort. Patients with high phosphorylated STAT3 (pSTAT3) within the TSPhigh group had higher influx of CD66b + cells and higher tumoral expression of PDL1. Bulk RNAseq of full section tumors showed enrichment of NFκB signaling and hypoxia in these cases. Spatial deconvolution through GeoMx® demonstrated higher expression of checkpoint and hypoxia-associated genes in the tumor (pan-cytokeratin positive) regions, and reduced lymphocyte receptor signaling in the TME (pan-cytokeratin- and αSMA-) and αSMA (pan-cytokeratin- and αSMA +) areas. Non-classical fibroblast signatures were detected across αSMA + regions in cases with high pSTAT3. Therefore, in this study we have shown that inhibition of JAK/STAT3 represents a promising therapeutic strategy for patients with stromal-rich CRC tumors. High expression of JAK/STAT3 proteins within both tumor and stromal cells predicts poor outcomes in CRC, and aberrant signaling is associated with distinct spatially-dependant differential gene expression.

Tumor-Stroma Proportion to Predict Chemoresistance in Patients With Ovarian Cancer

IMPORTANCE

Platinum-based chemotherapy is the backbone of standard-of-care treatment for patients with advanced-stage, high-grade serous carcinoma (HGSC), the most common form of ovarian cancer; however, one-third of patients have or acquire chemoresistance toward platinum-based therapies.

OBJECTIVE

To demonstrate the utility of tumor-stroma proportion (TSP) as a predictive biomarker of chemoresistance of HGSC, progression-free survival (PFS), and overall survival (OS).

DESIGN, SETTING, AND PARTICIPANTS

This prognostic study leveraged tumors from patients with HGSC in The Cancer Genome Atlas (TCGA) cohort (1993-2013) and an independent cohort of resected clinical specimens from patients with HGSC (2004-2014) available in diagnostic and tissue microarray formats from the University of Tübingen in Germany. Data analysis was conducted from January 2021 to January 2024.

EXPOSURE

Diagnosis of HGSC.

MAIN OUTCOMES AND MEASURES

Principal outcome measures were the ability of TSP to predict platinum chemoresistance, PFS, and OS. Using hematoxylin and eosin-stained slides from the Tübingen cohort (used for routine diagnostic assessment from surgical specimens) as well as tissue microarrays, representative sections of tumors for scoring of TSP were identified using previously evaluated cutoffs of 50% stroma or greater (high TSP) and less than 50% stroma (low TSP). Digitized slides from the TCGA Cohort were analyzed and scored in a similar fashion. Kaplan-Meier time-to-event functions were fit to estimate PFS and OS.

RESULTS

The study included 103 patients (mean [SD] age, 61.6 [11.1] years) from the TCGA cohort and 192 patients (mean [SD] age at diagnosis, 63.7 [11.1] years) from the Tübingen cohort. In the TCGA cohort, there was no significant association of TSP levels with chemoresistance, PFS, or OS. However, in the Tübingen cohort, high TSP was associated with significantly shorter PFS (HR, 1.586; 95% CI, 1.093-2.302; P = .02) and OS (hazard ratio [HR], 1.867; 1.249-2.789; P = .002). Patients with chemoresistant tumors were twice as likely to have high TSP as compared to patients with chemosensitive tumors (HR, 2.861; 95% CI, 1.256-6.515; P = .01). In tissue microarrays from 185 patients from the Tübingen cohort, high TSP was again associated with significantly shorter PFS (HR, 1.675; 95% CI, 1.012-2.772 P = .04) and OS (HR, 2.491; 95% CI, 1.585-3.912; P < .001).

CONCLUSIONS AND RELEVANCE

In this prognostic study, TSP was a consistent and reproducible marker of clinical outcome measures of HGSC, including PFS, OS, and platinum chemoresistance. Accurate and cost-effective predictive biomarkers of platinum chemotherapy resistance are needed to identify patients most likely to benefit from standard treatments, and TSP can easily be implemented and integrated into prospective clinical trial design and adapted to identify patients who are least likely to benefit long-term from conventional platinum-based cytotoxic chemotherapy treatment at the time of initial diagnosis.

The Complexity of Shapes: How the Circularity of Tumor Nodules Affects Prognosis in Colorectal Cancer

The current stratification of tumor nodules in colorectal cancer (CRC) staging is subjective and leads to high interobserver variability. In this study, the objective assessment of the shape of lymph node metastases (LNMs), extranodal extension (ENE), and tumor deposits (TDs) was correlated with outcomes. A test cohort and a validation cohort were included from 2 different institutions. The test cohort consisted of 190 cases of stage III CRC. Slides with LNMs and TDs were annotated and processed using a segmentation algorithm to determine their shape. The complexity ratio was calculated for every shape and correlated with outcomes. A cohort of 160 stage III CRC cases was used to validate findings. TDs showed significantly more complex shapes than LNMs with ENE, which were more complex than LNMs without ENE (P < .001). In the test cohort, patients with the highest sum of complexity ratios had significantly lower disease-free survival (P < .01). When only the nodule with the highest complexity was considered, this effect was even stronger (P < .001). This maximum complexity ratio per patient was identified as an independent prognostic factor in the multivariate analysis (hazard ratio, 2.47; P < .05). The trends in the validation cohort confirmed the results. More complex nodules in stage III CRC were correlated with significantly worse disease-free survival, even if only based on the most complex nodule. These results suggest that more complex nodules reflect more invasive tumor biology. As most of the more complex nodules were diagnosed as TDs, we suggest providing a more prominent role for TDs in the nodal stage and include an objective complexity measure in their definition.

Hypoxia signaling and metastatic progression

Disruption of oxygen homeostasis, resulting from an imbalance between O2 supply and demand during malignant proliferation, leads to the development of hypoxic tumor microenvironments that promote the acquisition of aggressive cancer cell phenotypes linked to metastasis and patient mortality. In this review, the mechanistic links between tumor hypoxia and metastatic progression are presented. Current status and perspectives of targeting hypoxia signaling pathways as a strategy to halt cancer cell metastatic activities are emphasized.

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

INTRODUCTION

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

Pathological determinants of outcome following resection of locally advanced or locally recurrent rectal cancer

INTRODUCTION

Pathological factors that influence and predict survival following pelvic exenteration (PE) for locally advanced (LARC) or locally recurrent rectal cancer (LRRC), especially LRRC, remain poorly understood. A clear resection margin has previously been demonstrated to be of most significance.

MATERIALS AND METHODS

A retrospective cohort study was performed for all patients undergoing a curative PE for LARC or LRRC between 2008 and 2021 at a tertiary referral UK specialist colorectal hospital. Cox regression analysis was planned to identify pathological factors associated with overall (OS), disease free (DFS) and local recurrence free survival (LRFS).

RESULTS

388 patients were included in the analysis with 256 resections for LARC and 132 for LRRC. 62.4% of patients were male with a median age of 59 years (IQR 49-67). 247 (64%) partial pelvic exenterations and 141 (36%) total pelvic exenterations performed. Overall R0 rate 86.6%. Poorly differentiated tumours and a positive resection margin independently influenced OS, DFS and LRFS on multivariate analysis in LARC. On multivariate analysis venous invasion negatively influenced DFS and poorly differentiated lesions negatively influenced LRFS in LRRC.

CONCLUSIONS

A positive resection margin and poorly differentiated tumours are significant negative prognostic markers for survival and recurrence in LARC. The results of this study support the need to look for alternative prognostic markers beyond that in the existing standard reporting dataset for rectal cancers. With increasing R0 rates, novel prognostic pathological markers are required to help guide treatment and surveillance for patients with LRRC.

Construction of a novel signature based on immune-related lncRNA to identify high and low risk pancreatic adenocarcinoma patients

BACKGROUND

Pancreatic adenocarcinoma is one of the most lethal tumors in the world with a poor prognosis. Thus, an accurate prediction model, which identify patients within high risk of pancreatic adenocarcinoma is needed to adjust the treatment and elevate the prognosis of these patients.

METHODS

We obtained RNAseq data of The Cancer Genome Atlas (TCGA) pancreatic adenocarcinoma (PAAD) from UCSC Xena database, identified immune-related lncRNAs (irlncRNAs) by correlation analysis, and identified differential expressed irlncRNAs (DEirlncRNAs) between pancreatic adenocarcinoma tissues from TCGA and normal pancreatic tissues from TCGA and Genotype-Tissue Expression (GTEx). Further univariate and lasso regression analysis were performed to construct prognostic signature model. Then, we calculated the areas under curve and identified the best cut-off value to identify high- and low-risk patients with pancreatic adenocarcinoma. The clinical characteristics, immune cell infiltration, immunosuppressive microenvironment, and chemoresistance were compared between high- and low-risk patients with pancreatic adenocarcinoma.

RESULTS

We identified 20 DEirlncRNA pairs and grouped the patients by the best cut-off value. We proved that our prognostic signature model possesses a remarkable efficiency to predict prognosis of PAAD patients. The AUC for ROC curve was 0.905 for 1-year prediction, 0.942 for 2-year prediction, and 0.966 for 3-year prediction. Patients in high-risk group have poor survival rate and worse clinical characteristics. We also proved that patients in high-risk groups were in immunosuppressive status and may be resistant to immunotherapy. Anti-cancer drug evaluation was performed based on in-silico predated tool, such as paclitaxel, sorafenib, and erlotinib, may be suitable for PAAD patients in high-risk group.

CONCLUSIONS

Overall, our study constructed a novel prognostic risk model based on pairing irlncRNAs, exhibited a promising prediction value in patients with pancreatic adenocarcinoma. Our prognostic risk model may help distinguish PAAD patients suitable for medical treatments.

Deep learning for the prediction of the chemotherapy response of metastatic colorectal cancer: comparing and combining H&E staining histopathology and infrared spectral histopathology

Colorectal cancer is a global public health problem with one of the highest death rates. It is the second most deadly type of cancer and the third most frequently diagnosed in the world. The present study focused on metastatic colorectal cancer (mCRC) patients who had been treated with chemotherapy-based regimen for which it remains uncertainty about the efficacy for all eligible patients. This is a major problem, as it is not yet possible to test different therapies in view of the consequences on the health of the patients and the risk of progression. Here, we propose a method to predict the efficacy of an anticancer treatment in an individualized way, using a deep learning model constructed on the retrospective analysis of the primary tumor of several patients. Histological sections from tumors were imaged by standard hematoxylin and eosin (HE) staining and infrared spectroscopy (IR). Images obtained were then processed by a convolutional neural network (CNN) to extract features and correlate them with the subsequent progression-free survival (PFS) of each patient. Separately, HE and IR imaging resulted in a PFS prediction with an error of 6.6 and 6.3 months respectively (28% and 26% of the average PFS). Combining both modalities allowed to decrease the error to 5.0 months (21%). The inflammatory state of the stroma seemed to be one of the main features detected by the CNN. Our pilot study suggests that multimodal imaging analyzed with deep learning methods allow to give an indication of the effectiveness of a treatment when choosing.

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.

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

OBJECTIVE

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

METHODS

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

RESULTS

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

CONCLUSION

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

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

AIM

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

MATERIALS AND METHODS

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

RESULTS

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

CONCLUSIONS

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

Clinical Significance of the Stromatic Component in Ovarian Cancer: Quantity Over Quality in Outcome Prediction

Background

The tumor stroma is composed of a complex network of non-cancerous cells and extracellular matrix elements that collectively are crucial for cancer progression and treatment response. Within the realm of ovarian cancer, the expression of the stromal gene cluster has been linked to poorer progression-free and overall survival rates. However, in the age of precision medicine and genome sequencing, the notion that the simple measurement of tumor-stroma proportion alone can serve as a biomarker for clinical outcome is a topic that continues to generate controversy and provoke discussion. Our current study reveals that it is the quantity of stroma, rather than its quality, that serves as a clinically significant indicator of patient outcome in ovarian cancer.

Methods

This study leveraged the High-Grade-Serous-Carcinoma (HGSC) cohort of the publicly accessible Cancer Genome Atlas Program (TCGA) along with an independent cohort comprising HGSC clinical specimens in diagnostic and Tissue Microarray formats. Our objective was to investigate the correlation between the Tumor-Stroma-Proportion (TSP) and progression-free survival (PFS), overall survival (OS), and response to chemotherapy. We assessed these associations using H&E-stained slides and tissue microarrays. Our analysis employed semi-parametric models that accounted for age, metastases, and residual disease as controlling factors.

Results

We found that high TSP (>50% stroma) was associated with significantly shorter progression-free survival (PFS) (p=0.016) and overall survival (OS) (p=0.006). Tumors from patients with chemoresistant tumors were twice as likely to have high TSP as compared to tumors from chemosensitive patients (p=0.012). In tissue microarrays, high TSP was again associated with significantly shorter PFS (p=0.044) and OS (p=0.0001), further confirming our findings. The Area Under the ROC curve for the model predicting platinum was estimated at 0.7644.

Conclusions

In HGSC, TSP was a consistent and reproducible marker of clinical outcome measures, including PFS, OS, and platinum chemoresistance. Assessment of TSP as a predictive biomarker that can be easily implemented and integrated into prospective clinical trial design and adapted to identify, at time of initial diagnosis, patients who are least likely to benefit long-term from conventional platinum-based cytotoxic chemotherapy treatment.

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.

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.

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.

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.

Deep learning in digital pathology for personalized treatment plans of cancer patients

Over the past decade, many new cancer treatments have been developed and made available to patients. However, in most cases, these treatments only benefit a specific subgroup of patients, making the selection of treatment for a specific patient an essential but challenging task for oncologists. Although some biomarkers were found to associate with treatment response, manual assessment is time-consuming and subjective. With the rapid developments and expanded implementation of artificial intelligence (AI) in digital pathology, many biomarkers can be quantified automatically from histopathology images. This approach allows for a more efficient and objective assessment of biomarkers, aiding oncologists in formulating personalized treatment plans for cancer patients. This review presents an overview and summary of the recent studies on biomarker quantification and treatment response prediction using hematoxylin-eosin (H&E) stained pathology images. These studies have shown that an AI-based digital pathology approach can be practical and will become increasingly important in improving the selection of cancer treatments for patients.

The Glasgow Microenvironment Score and risk and site of recurrence in TNM I-III colorectal cancer

BACKGROUND

Glasgow Microenvironment Score (GMS) stratifies long-term survival into three groups based on tumour phenotype: peritumoural inflammation (Klintrup-Mäkinen (KM)) and tumour stroma percentage (TSP). However, it is not known if the location of disease recurrence is influenced by the GMS category.

METHODS

Seven hundred and eighty-three TNM I-III colorectal cancers (CRC) were included. GMS (GMS0-high KM; GMS1-low KM, low TSP; GMS2-low KM, high TSP) and cancer-specific survival (CSS), overall survival (OS) and disease recurrence were assessed using Cox regression analysis.

RESULTS

Of the 783 patients, 221 developed CRC recurrence; 65 developed local recurrence + systemic disease. GMS was independent for CSS (HR 1.50, 95% CI 1.17-1.92, p < 0.001) and OS (HR 1.23, 1.05-1.44, p = 0.01). Higher GMS category was associated with T-stage, N-stage, emergency presentation and venous invasion. GMS was independent for local+systemic recurrence (HR 11.53, 95% CI 1.45-91.85, p = 0.04) and distant-only recurrence (HR 3.01, 95% CI 1.59-5.71, p = 0.002). GMS 2 disease did not appear to have statistically better outcomes with adjuvant chemotherapy in high-risk disease.

CONCLUSION

Although confounded by a higher rate of T4 and node-positive disease, GMS 1 and 2 are associated with an increased risk of local and distant recurrence. GMS is an independent poor prognostic indicator for recurrent colorectal cancer. Higher GMS patients may benefit from enhanced postoperative surveillance.

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

OBJECTIVE

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

MATERIAL AND METHOD

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

RESULTS

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

CONCLUSION

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

Prognostic value of desmoplastic stromal reaction, tumor budding and tumor-stroma ratio in stage II colorectal cancer

Background

Existing high-risk factors are insufficient to accurately predict the postoperative recurrence risk of stage II colorectal cancer (CRC). The discovery of additional prognostic markers may be the key to improving the current status of stage II CRC treatment. The present study aimed to evaluate the relationship among desmoplastic reaction (DR), tumor budding (TBd), the tumor-stroma ratio (TSR) and their prognostic value for relapse-free survival (RFS).

Methods

In this study, 207 patients with histologically confirmed stage II CRC from January 2012 to August 2018 were retrospectively reviewed from a single center; the cohort was divided into subgroups based on low or high TSR, and low, intermediate or high DR and TBd. Kaplan-Meier curve analysis and log-rank test were applied to examine RFS among subgroups. Univariate and multivariate Cox proportional hazards analyses were used to identify independent factors associated with RFS, and a nomogram was subsequently developed.

Results

Abnormal CA242, CEA, T4 stage, presence of hypertension, internal obstruction or perforation (IOP), lymphovascular or/and perineural invasion (PNI), number of nodes examined less than 12, low-frequency microsatellite instability (MSI-L), higher Ki-67 and immature DR were associated with a lower RFS. In multivariable analysis, DR (HR =2.111; 95% CI: 1.184-3.766; P=0.011), LVI (HR =1.919; 95% CI: 1.004-3.669; P=0.049) and PNI (HR =2.724; 95% CI: 1.362-5.448; P=0.005) were prognostic factors for RFS. On this basis, a nomogram that integrated DR and clinicopathologic predictors for predicting RFS passed the calibration and had an area under the curve of 0.826.

Conclusions

The prognostic significance of DR outperformed TBd and TSR, therefore, we recommend adding DR as a biomarker in routine pathological reports. The novel nomogram combining these factors may be used as a reliable and effective tool for the prediction of RFS in stage II CRC, thus helping optimize therapeutic regimens under cooperation of oncologists and surgeons. Further multicentric studies are required for validation of this novel, simple and cost-effective prognostic model.

Peritumoral tertiary lymphoid structure and tumor stroma percentage predict the prognosis of patients with non-metastatic colorectal cancer

Background

Tertiary lymphoid structures (TLSs) are crucial in promoting and maintaining positive anti-tumor immune responses. The tumor stroma has a powerful immunosuppressive function that could exclude tumor-infiltrating lymphocytes from the tumor beds and lead to a “cold” phenotype. TLSs and tumor stroma percentage (TSP) are significantly associated with the prognosis of patients with certain cancers. However, the exact roles of TLSs and TSP and their intrinsic relationship are still largely unknown in colorectal cancer (CRC).

Methods

TLSs and TSP were assessed using hematoxylin-eosin (H&amp;E) and/or immunohistochemistry (IHC) staining from 114 CRC patients in the training set and 60 CRC patients in the external validation set. The correlation between TILs, TLS and clinicopathological characteristics and their prognostic values were assessed. Finally, we plotted a Nomogram including the TLS, TSP and tumor-node-metastasis (TNM) stage to predict the probability of recurrence-free survival (RFS) at 2- and 5-years in non-metastatic colorectal cancer (nmCRC) patients.

Results

Peritumoral TLS (P-TLS), intratumoral TLS (In-TLS) and high TSP (H-TSP, &gt;50%) were present in 99.1%, 26.3% and 41.2% patients, respectively. H-TSP tumor tends to be associated with lower P-TLS density (P =0.0205). The low P-TLS density (&lt; 0.098/mm2) was significantly associated with reduced RFS (HR=6.597 95% CI: 2.882-15.103, P &lt;0.001) and reduced overall survival (OS) (HR=6.628 95% CI: 2.893-15.183, P &lt; 0.001) of nmCRC patients. In-TLS was not of significance in evaluating the clinical outcomes of nmCRC patients. H-TSP was significantly associated with reduced RFS (HR=0.126 95% CI: 0.048-0.333, P &lt;0.001) and reduced OS (HR=0.125 95% CI: 0.047-0.332, P &lt;0.001) of nmCRC patients. The 5-year RFS of the high P-TLS, low-TLS, H-TSP, and L-TSP groups were 89.7%, 47.2%, 53.2%, and 92.5%, respectively. The P-TLS density, TSP and TNM stage were independent prognosis factors of nmCRC patients. The Nomogram, including the P-TLS density, TSP and TNM stage, outperformed the TNM stage.

Conclusions

High P-TLS density and low TSP (L-TSP) were independent and favorable prognostic factors of nmCRC patients, which might provide new directions for targeted therapy in the CRC tumor microenvironment, especially the tumor immune microenvironment.

A systematic review of the pathological determinants of outcome following resection by pelvic exenteration of locally advanced and locally recurrent rectal cancer

BACKGROUND

Despite multimodal therapy 5-15% of patients who undergo resection for advanced rectal cancer (LARC) will develop local recurrence. Management of locally recurrent rectal cancer (LRRC) presents a significant therapeutic challenge and even with modern exenterative surgery, 5-year survival rates are poor at 25-50%. High rates of local and systemic recurrence in this cohort are reflective of the likely biological aggressiveness of these tumour types. This review aims to appraise the current literature identifying pathological factors associated with survival and tumour recurrence in patients undergoing exenterative surgery.

METHODS

A systematic review was carried out searching MEDLINE, EMBASE and COCHRANE Trials database for all studies assessing pathological factors influencing survival following pelvic exenteration for LARC or LRRC from 2010 to July 2021 following PRISMA guidelines. Risk of bias was assessed using QUIPS tool.

RESULTS

Nine cohort studies met inclusion criteria, reporting outcomes for 2864 patients. Meta-analysis was not possible due to significant heterogeneity of reported outcomes. Resection margin status and nodal disease were the most commonly reported factors. A positive resection margin was demonstrated to be a negative prognostic marker in six studies. Involved lymph nodes and lymphovascular invasion also appear to be negative prognostic markers with tumour stage to be of lesser importance. No studies assessed other adverse tumour features that would not otherwise be included in a standard histopathology report.

CONCLUSION

Pathological resection margin status is widely demonstrated to influence disease free and overall survival following pelvic exenteration for rectal cancer. With increasing R0 rates, other adverse tumour features must be explored to help elucidate differences in survival and potentially guide tailored oncological treatment.

Polarimetric biomarkers of peri-tumoral stroma can correlate with 5-year survival in patients with left-sided colorectal cancer

Using a novel variant of polarized light microscopy for high-contrast imaging and quantification of unstained histology slides, the current study assesses the prognostic potential of peri-tumoral collagenous stroma architecture in 32 human stage III colorectal cancer (CRC) patient samples. We analyze three distinct polarimetrically-derived images and their associated texture features, explore different unsupervised clustering algorithm models to group the data, and compare the resultant groupings with patient survival. The results demonstrate an appreciable total accuracy of ~ 78% with significant separation (p < 0.05) across all approaches for the binary classification of 5-year patient survival outcomes. Surviving patients preferentially belonged to Cluster 1 irrespective of model approach, suggesting similar stromal microstructural characteristics in this sub-population. The results suggest that polarimetrically-derived stromal biomarkers may possess prognostic value that could improve clinical management/treatment stratification in CRC patients.

Intratumoral Budding in Pretreatment Biopsies, among Tumor Microenvironmental Components, Can Predict Prognosis and Neoadjuvant Therapy Response in Colorectal Adenocarcinoma

Background and Objectives: The prediction of the prognosis and effect of neoadjuvant therapy is vital for patients with advanced or unresectable colorectal carcinoma (CRC). Materials and Methods: We investigated several tumor microenvironment factors, such as intratumoral budding (ITB), desmoplastic reaction (DR), and Klintrup–Mäkinen (KM) inflammation grade, and the tumor–stroma ratio (TSR) in pretreatment biopsy samples (PBSs) collected from patients with advanced or unresectable CRC. A total of 85 patients with 74 rectal carcinomas and 11 colon cancers treated at our hospital were enrolled; 66 patients had curative surgery and 19 patients received palliative treatment. Results: High-grade ITB was associated with recurrence (p = 0.002), death (p = 0.034), and cancer-specific death (p = 0.034). Immature DR was associated with a higher grade of clinical tumor-node-metastasis stage (cTNM) (p = 0.045), cN category (p = 0.045), and cM category (p = 0.046). The KM grade and TSR were not related to any clinicopathological factors. High-grade ITB had a significant relationship with tumor regression in patients who received curative surgery (p = 0.049). Conclusions: High-grade ITB in PBSs is a potential unfavorable prognostic factor for patients with advanced CRC. Immature DR, TSR, and KM grade could not predict prognosis or therapy response in PBSs.

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.

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.

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.

Combinatory statuses of tumor stromal percentage and tumor infiltrating lymphocytes as prognostic factors in stage III colorectal cancers

BACKGROUND AND AIM

Tumor stroma and tumor-infiltrating lymphocytes (TILs) are major constituents of the tumor microenvironment, although they have different effects on the prognosis of patients with colorectal cancer (CRC). Combinatory statuses of tumor-stromal percentage (TSP) and TILs are expected to provide more powerful prognostic information but have never been studied in CRCs.

METHODS

Stage III CRCs from patients (n = 487) treated with adjuvant chemotherapy were assessed for their TSP and CD3-TIL or CD8-TIL densities using computer-aided methodology. With cut-off values set at median values for intraepithelial TIL (iTIL) and stromal TIL (sTIL) densities, CRCs were sorted into low and high iTIL or sTIL groups. CRCs were classified into five quintile (Q1-Q5) groups according to their TSP and divided into high TSP (Q5) and low TSP (Q1-4) groups.

RESULTS

The combination of CD8 iTIL density and TSP was found to be an independent prognostic parameter in multivariate survival analysis in terms of cancer-specific survival and recurrence-free survival. CRCs with low CD8 iTIL density and high TSP showed the worst survival. The combinatory status showed more prognostic power than CD8 iTIL density or TSP alone. Multivariate survival analysis in an independent cohort of stage III CRC validated the prognostic power of the combinatory statuses.

CONCLUSIONS

The findings suggest that the combinatory status might serve as a prognostic parameter in stage III CRCs. Further research in a large-scale cohort of patients with stage III CRC is needed to validate the prognostic power of the combinatory status.

Stromal scoring in advanced colon and rectal cancer: Stroma-rich tumors and their association with aggressive phenotypes

Background: Our aim was to explore relevance of the proportion between neoplastic cell component and tumor-associated stroma in order to assess its association with confirmed aggressive phenotypes of right/left colon and rectum cancers in a large series of patients. Methods: The quantification of stroma component was performed in patients diagnosed with colorectal adenocarcinoma who underwent surgical resection. The analyzed variables were age, gender, anatomical/pathological features, and tumor-stroma proportion. Tumor-stroma proportion was estimated based on slides used in routine pathology for determination of T status and was described as low, with a stromal percentage ?50% or high, with a stromal percentage >50%. The tumor-stroma proportion was estimated by two observers, and the inter-observer agreement was assessed. Results: The sample included 390 colorectal adenocarcinoma patients. Stroma-rich tumors were observed in 53.3% of cases. Well-differentiated tumors had the lowest stromal proportions (p = 0.028). Stroma-poor tumors showed less depth of invasion (p<0.001). High stromal content was observed in association with tumor budding, perineural, angiolymphatic, and lymph node involvement, and distant metastasis (p?0.001). Colorectal adenocarcinoma without lymph node or distant metastasis involvement had lower stromal proportion, while metastatic ones exhibited high stromal content (p <0.001). The inter-rater reliability (concordance) between the estimations of pathologists for tumor-stroma proportions was high (?=0.746). Conclusion: The tumorstroma proportion in colorectal adenocarcinoma was associated with adverse prognostic factors, reflecting the stage of the disease. Stroma-rich tumors showed a significant correlation with advancement of the disease and its aggressiveness. Due to its availability tumor-stroma proportion evaluation has high application potential and can complement current staging system for colorectal adenocarcinoma.

Automated assessment of DNA ploidy, chromatin organization, and stroma fraction to predict prognosis and adjuvant therapy response in patients with stage II colorectal carcinoma

DNA ploidy, tumor stroma, and chromatin organization have important implications in tumorigenesis and patient outcome. Automated image cytometry tools were developed to quantitatively measure DNA ploidy (P), stroma fraction (S), and chromatin organization or Nucleotyping (N). This study aimed to discover their clinical value in different stages of colorectal cancer (CRC) in a Chinese patient population. A total of 496 CRC patients of stages I, II, and LMCRC (liver metastatic CRC) were enrolled in this study. Stage II CRC patients with diploidy, low-stroma, or chromatin homogenous status predicted significantly higher 5-year OS and DFS. We constructed a PSN-panel enabled the stage II patients to be further stratified into low-, middle-, high-risk groups, the 5-year OS (89.5% vs 67.9% vs 60.9%, P<0.001) and DFS (86.0% vs 62.3% vs 53.6%, P<0.001) were stratified significantly. In addition, when combined the PSN-panel with T stage or MSS status in stage II patients, the PSN-low risk patients showed significant longer 5-year OS and DFS than the PSN-high risk patients in T3 (OS: 86.3% vs 65.3%, P=0.015; DFS: 83.5 vs 59.8%, P=0.013) or MSS (OS: 86.4% vs 63.9%, P=0.005; DFS: 85.5 vs 57.8%, P=0.003) patients. Finally, in the group of stage II patients with at least one high-risk factor (non-diploidy, high-stroma, chromatin heterogenous), patients who received adjuvant therapy showed significantly longer OS (72.1% vs 48.3%, P=0.007) and DFS (64.5% vs 43.9%, P=0.015) than those who did not receive adjuvant therapy. In contrast, P, S, N couldn't predict the prognosis of stage I and LMCRC patients. Overall, our data demonstrate that the PSN panel is an accurate prognostic tool that can guide treatment decisions for Chinese stage II CRC patients.

A classification based on tumor-stroma ratio and tumor budding for patients with muscle-invasive bladder cancer

BACKGROUND

Tumor-stroma ratio (TSR) and tumor budding (TB) play important roles in muscle-invasive bladder cancer (MIBC). We developed a rating system (TSR-TB type) based on the morphological evaluation of TSR and TB for predicting patient outcome and using individualized care.

METHODS

TSR and TB were assessed in publicly accessible MIBC tumor slides from the TCGA database. MIBC patients were classified as low stromal or high stromal type based on TSR, and high stromal type was further classified as compartmentalized or mixed stromal type based on TB.

RESULTS

TSR-TB type was an independent adverse prognostic factor for OS (P < 0.001). Low stromal type had a greater prognosis (P < 0.001) and were enriched for FGFR3 mutations (P = 0.001). The mixed stromal type was distinguished by increased M2 macrophage penetration (P < 0.001), anti-tumor immune activity, DNA repair pathway mutations, and poor survival. GSEA showed that certain cancer-related pathways, such as mitotic spindle, PI3K-AKT-MTOR signalingwere hyperactivated in high stromal type (all FDR<0.05). Furthermore, mixed stromal type demonstrated enhanced activation of epithelial mesenchymal transformation (EMT), inflammatory response (all FDR<0.05).

CONCLUSION

TSR and TB-based MIBC classification coincides with patient survival and molecular alterations. The identified subtypes may have important implications for individualized MIBC therapy.

Development and Validation of the Individualized Prognostic Nomograms in Patients With Right- and Left-Sided Colon Cancer

Background

The overall survival (OS) of patients diagnosed with colon cancer (CC) varied greatly, so did the patients with the same tumor stage. We aimed to design a nomogram that is capable of predicting OS in resected left-sided colon cancers (LSCC) and right-sided colon cancers (RSCC), and thus to stratify patients into different risk groups, respectively.

Methods

Records from a retrospective cohort of 577 patients with complete information were used to construct the nomogram. Univariate and multivariate analyses screened risk factors associated with overall survival. The performance of the nomogram was evaluated with concordance index (c-index), calibration plots, and decision curve analyses for discrimination, accuracy, calibration ability, and clinical net benefits, respectively, which was further compared with the American Joint Committee on Cancer (AJCC) 8th tumor-node-metastasis (TNM) classification. Risk stratification based on nomogram scores was performed with recursive partitioning analysis.

Results

The LSCC nomogram incorporated carbohydrate antigen 12-5 (CA12-5), age and log odds of positive lymph nodes (LODDS), and RSCC nomogram enrolled tumor stroma percentage (TSP), age and LODDS. Compared with the TNM classification, the LSCC and RSCC nomograms both had a statistically higher C-index (0.837, 95% CI: 0.827-0.846 and 0.780, 95% CI 0.773-0.787, respectively) and more clinical net benefits, respectively. Calibration plots revealed no deviations from reference lines. All results were reproducible in the validation cohort.

Conclusions

An original predictive nomogram was constructed and validated for OS in patients with CC after surgery, which had facilitated physicians to appraise the individual survival of postoperative patients accurately and to identify high-risk patients who were in need of more aggressive treatment and follow-up strategies.

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

BACKGROUND

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

METHODS

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

RESULTS

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

CONCLUSION

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

The Crohn's-like lymphoid reaction density: a new artificial intelligence quantified prognostic immune index in colon cancer

BACKGROUND

The Crohn's-like lymphoid reaction (CLR) is manifested as peritumoral lymphocytes aggregation in colon cancer, which is a major component of the host immune response to cancer. However, the lack of a unified and objective CLR evaluation standard limits its clinical application. We, therefore, developed a deep learning model for the fully automated CLR density quantification on routine hematoxylin and eosin (HE)-stained whole-slide images (WSIs) and further investigated its prognostic validity for patient stratification.

METHODS

The CLR density was calculated by using a deep learning method on HE-stained WSIs. A training (N = 279) and a validation (N = 194) cohorts were used to evaluate the prognostic value of CLR density for overall survival (OS).

RESULT

The fully automated quantified CLR density was an independent prognostic factor, with high CLR density associated with increased OS in the discovery (HR 0.58, 95% CI 0.38-0.89, P = 0.012) and validation cohort (0.45, 0.23-0.88, 0.020). Integrating CLR density into a Cox model with other risk factors showed improved prognostic capability.

CONCLUSION

We developed a new immune indicator (CLR density) quantified by a deep learning method to evaluate the lymphocytes aggregation in colon cancer. The CLR density was demonstrated its predictive value for OS in two independent cohorts. This approach allows for the objective and standardized quantification while reducing pathologists' workload. Therefore, this fully automated standardized method of CLR evaluation had potential clinical value.

Semiautomatic analysis of tumor proportion in colon cancer: Lessons from a validation study

The tumor stroma ratio (TSR) is a promising histopathologic prognostic biomarker, which could allow for more accurate risk stratification and improved patient management in colorectal cancer. The purpose of our research was to validate the results of a previous study, which had suggested that not only a low but also a high tumor proportion (TP) might be an independent risk factor for occurrence of distant metastasis and worse overall survival using a semiautomatic image analysis approach with the open-source software ImageJ. We investigated 253 pT3 and pT4 adenocarcinomas of no special type. The previously established thresholds (PES-cut-offs) used to classify the patients (previous 3-tiered-classification) according to the tumor proportion (TP) in a highTP (TP ≥ 54%), a mediumTP (TP < 54% ∩ TP >15%) and a lowTP (TP ≤ 15%) group did not show a significant risk stratification. Even the adjustment of these threshold revealed no significant results. Therefore, a receiver-operating characteristic (ROC) analysis was performed to establish the cut-off with the most significant predictive power and a "new 2-tiered-classification" using this cut-off (40% at MinTP) showed a significantly shorter absence of metastasis for patients with a low TP (p = 0.007). These results confirm that a low TP is associated with an adverse prognosis. This study did not confirm the previous assumption that a high TP might also be a risk factor for occurrence of metastasis. Furthermore, it demonstrates that this semiautomatic technique is not superior to the established method, so that approaches to enhance prognostic techniques should continue.

[Assessment of the metastatic potential of localized forms of colorectal cancer]

OBJECTIVE

To assess the risk of recurrence after surgical treatment is an integral part of the management of patients with colorectal cancer. The AJCC/UICC TNM staging system, in which the risk is identified by grouping the patients on the basis of anatomical elements, is commonly used. Despite the simplicity of implementation, significant heterogeneity remains within each stage group. A better tool for predicting a recurrence is needed in the era of multimodal treatment.

SUBJECTS AND METHODS

A total of 1350 archival colorectal cancer cases during 2012 to 2015 were retrospectively analyzed; among which the investigators identified 3 patient groups: 1) 53 patients with non-metastatic colon cancer for at least 5 years; 2) 45 patients with metachronous metastases detected during the same period; and 3) 53 patients with synchronous metastases. Among the estimated 31 parameters, the investigators used a multidimensional analysis to select 6 most significant prognostic factors that were included in the final model based on a logistic regression analysis. The resulting model was applied to assess the risk of metastasis after cytoreductive surgery. It was internally and externally validated in an examination group (n=25).

RESULTS

The model has a sensitivity of 97.78% and a specificity of 96.23%, improving the risk stratification for metastatic colon cancer. The factors in the model include extramural venous invasion, the severity of budding, the expression of E-cadherin and β-catenin, the proportion of cytotoxic CD8⁺ lymphocytes of the total number of T lymphocytes in the microenvironment, and the ratio of newly formed vessels to tumor stromal microvessel density.

CONCLUSION

Using morphopathological factors, the resulting model allows better consideration of tumor specificity in a particular patient, thereby providing a more individual prediction of outcome than that provided by the AJCC/UICC TNM staging system. By identifying patients at both high- and low-risk for metastasis, the model can be useful to plan treatment and to choose clinical management tactics for patients with colorectal cancer.

Global colorectal cancer burden in 2020 and projections to 2040

As the third most common malignancy and the second most deadly cancer, colorectal cancer (CRC) induces estimated 1.9 million incidence cases and 0.9 million deaths worldwide in 2020. The incidence of CRC is higher in highly developed countries, and it is increasing in middle- and low-income countries due to westernization. Moreover, a rising incidence of early-onset CRC is also emerging. The large number of CRC cases poses a growing global public health challenge. Raising awareness of CRC is important to promote healthy lifestyle choices, novel strategies for CRC management, and implementation of global screening programs, which are critical to reducing CRC morbidity and mortality in the future. CRC is a heterogeneous disease, and its subtype affiliation influences prognosis and therapeutic response. An accurate CRC subtype classification system is of great significance for basic research and clinical outcome. Here, we present the global epidemiology of CRC in 2020 and projections for 2040, review the major CRC subtypes to better understand CRC molecular basis, and summarize current risk factors, prevention, and screening strategies for CRC.