Prognostic value of nucleotyping, DNA ploidy and stroma in high-risk stage II colon cancer

Personalizing adjuvant therapy for patients with colorectal cancer

The current standard-of-care adjuvant treatment for patients with colorectal cancer (CRC) comprises a fluoropyrimidine (5-fluorouracil or capecitabine) as a single agent or in combination with oxaliplatin, for either 3 or 6 months. Selection of therapy depends on conventional histopathological staging procedures, which constitute a blunt tool for patient stratification. Given the relatively marginal survival benefits that patients can derive from adjuvant treatment, improving the safety of chemotherapy regimens and identifying patients most likely to benefit from them is an area of unmet need. Patient stratification should enable distinguishing those at low risk of recurrence and a high chance of cure by surgery from those at higher risk of recurrence who would derive greater absolute benefits from chemotherapy. To this end, genetic analyses have led to the discovery of germline determinants of toxicity from fluoropyrimidines, the identification of patients at high risk of life-threatening toxicity, and enabling dose modulation to improve safety. Thus far, results from analyses of resected tissue to identify mutational or transcriptomic signatures with value as prognostic biomarkers have been rather disappointing. In the past few years, the application of artificial intelligence-driven models to digital images of resected tissue has identified potentially useful algorithms that stratify patients into distinct prognostic groups. Similarly, liquid biopsy approaches involving measurements of circulating tumour DNA after surgery are additionally useful tools to identify patients at high and low risk of tumour recurrence. In this Perspective, we provide an overview of the current landscape of adjuvant therapy for patients with CRC and discuss how new technologies will enable better personalization of therapy in this setting.

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.

Deep-Learning-Based Hepatic Ploidy Quantification Using H&E Histopathology Images

Polyploidy, the duplication of the entire genome within a single cell, is a significant characteristic of cells in many tissues, including the liver. The quantification of hepatic ploidy typically relies on flow cytometry and immunofluorescence (IF) imaging, which are not widely available in clinical settings due to high financial and time costs. To improve accessibility for clinical samples, we developed a computational algorithm to quantify hepatic ploidy using hematoxylin-eosin (H&E) histopathology images, which are commonly obtained during routine clinical practice. Our algorithm uses a deep learning model to first segment and classify different types of cell nuclei in H&E images. It then determines cellular ploidy based on the relative distance between identified hepatocyte nuclei and determines nuclear ploidy using a fitted Gaussian mixture model. The algorithm can establish the total number of hepatocytes and their detailed ploidy information in a region of interest (ROI) on H&E images. This is the first successful attempt to automate ploidy analysis on H&E images. Our algorithm is expected to serve as an important tool for studying the role of polyploidy in human liver disease.

DNA ploidy and stroma predicted the risk of recurrence in low-risk stage III colorectal cancer

BACKGROUND

For clinically low-risk stage III colorectal cancer, the decision on cycles of adjuvant chemotherapy after surgery is disputed. The present study investigates the use of additional biomarkers of ploidy and stroma-ratio(PS) to stratify patients with low-risk stage III colorectal cancer, providing a basis for individualized treatment in the future.

METHODS

This study retrospectively enrolled 198 patients with clinical-low-risk stage III colorectal cancer (T1-3N1M0) and analyzed the DNA ploidy and stroma ratio of FFPE tumor tissues. The patients were divided into PS-low-risk group (Diploidy or Low-stroma) and PS-high-risk group (Non-diploid and High-stroma). For survival analyses, Kaplan-Meier and Cox regression models were used.

RESULTS

The results showed that the 5-year DFS of the PS-high-risk group was significantly lower than that in the PS-low-risk group (78.6 vs. 91.2%, HR = 2.606 [95% CI: 1.011-6.717], P = 0.039). Besides, in the PS-low-risk group, the 5 year OS (98.2 vs. 86.7%, P = 0.022; HR = 5.762 [95% CI: 1.281-25.920]) and DFS (95.6, vs 79.9%, P = 0.019; HR = 3.7 [95% CI: 1.24-11.04]) of patients received adjuvant chemotherapy for > 3 months were significantly higher than those received adjuvant chemotherapy for < 3 months. We also found that the PS could stratify the prognosis of patients with dMMR tumors. The 5-year OS (96.3 vs 71.4%, P = 0.037) and DFS (92.6 vs 57.1%, P = 0.015) were higher in the PS-low-risk dMMR patients than those in the PS-high-risk dMMR patients.

CONCLUSION

In this study, we found that PS can predict the prognosis of patients with stage III low-risk CRC. Besides, it may guide the decision on postoperative adjuvant chemotherapy.

A retrospective analysis using deep-learning models for prediction of survival outcome and benefit of adjuvant chemotherapy in stage II/III colorectal cancer

PURPOSE

Most of Stage II/III colorectal cancer (CRC) patients can be cured by surgery alone, and only certain CRC patients benefit from adjuvant chemotherapy. Risk stratification based on deep-learning from haematoxylin and eosin (H&E) images has been postulated as a potential predictive biomarker for benefit from adjuvant chemotherapy. However, very limited success has been achieved in using biomarkers, including deep-learning-based markers, to facilitate the decision for adjuvant chemotherapy despite recent advances of artificial intelligence.

METHODS

We trained and internally validated CRCNet using 780 Stage II/III CRC patients from Molecular and Cellular Oncology. Independent external validation of the model was performed using 337 Stage II/III CRC patients from The Cancer Genome Atlas (TCGA).

RESULTS

CRCNet stratified the patients into high, medium, and low-risk subgroups. Multivariate Cox regression analyses confirmed that CRCNet risk groups are statistically significant after adjusting for existing risk factors. The high-risk subgroup significantly benefits from adjuvant chemotherapy. A hazard ratio (chemo-treated vs untreated) of 0.2 (95% Confidence Interval (CI), 0.05-0.65; P = 0.009) and 0.6 (95% CI 0.42-0.98; P = 0.038) are observed in the TCGA and MCO Fluorouracil-treated patients, respectively. Conversely, no significant benefit from chemotherapy is observed in the low- and medium-risk groups (P = 0.2-1).

CONCLUSION

The retrospective analysis provides further evidence that H&E image-based biomarkers may potentially be of great use in delivering treatments following surgery for Stage II/III CRC, improving patient survival, and avoiding unnecessary treatment and associated toxicity, and warrants further validation on other datasets and prospective confirmation in clinical trials.

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.

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).

Prognostic value of a novel biomarker combining DNA ploidy and tumor burden score for initially resectable liver metastases from patients with colorectal cancer

Background

Colorectal cancer liver metastases (CRLM) has not been identified as a unified disease entity due to the differences in the severity of metastatic disease and tumor aggressiveness. A screen for specific prognostic risk subgroups is urgently needed. The current study aimed to investigate the prognostic value of DNA ploidy, stroma fraction and nucleotyping of initially resectable liver metastases from patients with CRLM.

Methods

One hundred thirty-nine consecutive patients with initially resectable CRLM who underwent curative liver resection from 2006 to 2018 at Sun Yat-sen University Cancer Center were selected for analysis. DNA ploidy, stroma fraction and nucleotyping of liver metastases were evaluated using automated digital imaging systems. Recurrence-free survival (RFS) and overall survival (OS) were analyzed using the Kaplan-Meier method and Cox regression models.

Results

DNA ploidy was identified as an independent prognostic factor for RFS (HR, 2.082; 95% CI 1.053–4.115; P = 0.035) in the multivariate analysis, while stroma-tumor fraction and nucleotyping were not significant prognostic factors. A significant difference in 3-year RFS was observed among the low-, moderate- and high-risk groups stratified by a novel parameter combined with the tumor burden score (TBS) and DNA ploidy (72.5% vs. 63.2% vs. 37.3%, P = 0.007). The high-risk group who received adjuvant chemotherapy had a significantly better 3-year RFS rate than those without adjuvant chemotherapy (46.7% vs. 24.8%; P = 0.034).

Conclusions

Our study showed that DNA ploidy of liver metastases is an independent prognostic factor for patients with initially resectable CRLM after liver resection. The combination of DNA ploidy and TBS may help to stratify patients into different recurrence risk groups and may guide postoperative treatment among the patients.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12935-021-02250-x.

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

Background

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

Methods

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

Results

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

Conclusion

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

Prognostic Value of the Diversity of Nuclear Chromatin Compartments in Gynaecological Carcinomas

Statistical texture analysis of cancer cell nuclei stained for DNA has recently been used to develop a pan-cancer prognostic marker of chromatin heterogeneity. In this study, we instead analysed chromatin organisation by automatically quantifying the diversity of chromatin compartments in cancer cell nuclei. The aim was to investigate the prognostic value of such an assessment in relation to chromatin heterogeneity and as a potential supplement to pathological risk classifications in gynaecological carcinomas. The diversity was quantified by calculating the entropy of both chromatin compartment sizes and optical densities within compartments. We analysed a median of 281 nuclei (interquartile range (IQR), 273 to 289) from 246 ovarian carcinoma patients and a median of 997 nuclei (IQR, 502 to 1452) from 791 endometrial carcinoma patients. The prognostic value of the entropies and chromatin heterogeneity was moderately strongly correlated (r ranged from 0.68 to 0.73), but the novel marker was observed to provide additional prognostic information. In multivariable analysis with clinical and pathological markers, the hazard ratio associated with the novel marker was 2.1 (95% CI, 1.3 to 3.5) in ovarian carcinoma and 2.4 (95% CI, 1.5 to 3.9) in endometrial carcinoma. Integration with pathological risk classifications gave three risk groups with distinctly different prognoses. This suggests that the novel marker of diversity of chromatin compartments might possibly contribute to the selection of high-risk stage I ovarian carcinoma patients for adjuvant chemotherapy and low-risk endometrial carcinoma patients for less extensive surgery.