The relationship between stroma AReactive invasion front areas (SARIFA), warburg-subtype and survival: results from a large prospective series of colorectal cancer patients

BACKGROUND: Stroma AReactive Invasion Front Areas (SARIFA) is a recently identified haematoxylin & eosin (H&E)based histopathologic biomarker in gastrointestinal cancers, including colorectal cancer (CRC), defined as direct contact between tumour cells and adipocytes at the tumour invasion front. The current study aimed at validating the prognostic relevance of SARIFA in a large population-based CRC series as well as at investigating the relationship between SARIFA-status and previously established Warburg-subtypes, both surrogates of the metabolic state of the tumour cells. METHODS: SARIFA-status (positive versus negative) was determined on H&E slides of 1,727 CRC specimens. Warburg-subtype (high versus moderate versus low) data was available from our previous study. The associations between SARIFA-status, Warburg-subtype, clinicopathological characteristics and CRC-specific as well as overall survival were investigated. RESULTS: 28.7% (n=496) CRC were SARIFA-positive. SARIFA-positivity was associated with more advanced disease stage, higher pT category, and more frequent lymph node involvement (all p<0.001). SARIFA-positivity was more common in Warburg-high CRC. 44.2% (n=219) of SARIFA-positive CRCs were Warburg-high compared to 22.8% (n=113) being Warburg-low and 33.1% (n=164) being Warburg-moderate (p<0.001). In multivariable-adjusted analysis, patients with SARIFA-positive CRCs had significantly poorer CRC-specific (HR 1.65; 95% CI 1.41-1.93) and overall survival (HR 1.46; 95% CI 1.28-1.67) independent of clinically known risk factors and independent of Warburg-subtype. Combining the SARIFA-status and the Warburg-subtype to a combination score (SARIFA-negative/Warburg-high versus SARIFA-positive/Warburg-low versus SARIFA-positive/Warburg-high, and so on) did not improve the survival prediction compared to the use of SARIFA-status alone (SARIFA-negative + Warburg-high: HR 1.08; 95% CI 0.84-1.38; SARIFA-positive + Warburg-low: HR 1.79; 95% CI 1.32-2.41; SARIFA-positive + Warburg-high: HR 1.58; 95% CI 1.23-2.04). CONCLUSIONS: Our current study is the by far largest external validation of SARIFA-positivity as a novel independent negative prognostic H&E-based biomarker in CRC. In addition, our study shows that SARIFA-positivity is associated with the Warburg-high subtype. Further research is warranted to provide a more mechanistic understanding of the underlying tumour biology. Based on our data, we conclude SARIFA-status should be implemented in pathologic routine practice to stratify CRC patients

Association between long-term energy balance-related factors and survival in colorectal cancer overall and by metabolic Warburg-subtypes

BACKGROUND: Long-term energy balance-related factors (i.e., lifestyle and physiologic factors that influence the equilibrium between energy intake and energy expenditure over an extended period) such as body mass index (BMI) are linked to colorectal cancer risk, but their impact on colorectal cancer survival is unclear. We explored associations between these long-term energy balance-related factors and survival and examined potential differences across metabolic Warburg-subtypes. METHODS: Associations between long-term energy balance-related factors and survival in the total series of patients with colorectal cancer (n = 2,347) obtained from the prospective Netherlands Cohort Study, as well as according to Warburg-subtype (Warburg-low: n = 652, Warburg-moderate: n = 802, Warburg-high: n = 797), were investigated using Cox regression analysis. RESULTS: Among the long-term energy balance-related factors studied, only increasing prediagnostic BMI was associated with a borderline significant poorer overall survival in patients with colorectal cancer [HR5kg/m2, 1.07; 95% confidence interval (CI), 0.99-1.15]. Stratified analyses showed that prediagnostic weight gain (HR5kg, 1.04; 95% CI, 0.99-1.09) and potentially increased height (HR5cm, 1.04; 95% CI, 0.98-1.11) were associated with poor overall survival only in patients with Warburg-high colorectal cancer. Increasing prediagnostic BMI was associated with poor survival only in patients with Warburg-moderate colorectal cancer (colorectal cancer-specific: HR5kg/m2, 1.12; 95% CI, 0.96-1.32; overall: HR5kg/m2, 1.20; 95% CI, 1.05-1.36). No consistent patterns were observed across energy restriction proxies. CONCLUSIONS: Maintaining a healthy prediagnostic BMI may be beneficial for colorectal cancer survival. Moreover, associations between prediagnostic BMI, weight change, early-life energy restriction, height, and colorectal cancer survival differed according to Warburg-subtypes. IMPACT: Understanding the biologic pathways involved in associations between energy balance-related factors and colorectal cancer survival could help refine prevention strategies in the future.</p

Fully transformer-based biomarker prediction from colorectal cancer histology: a large-scale multicentric study

Background: Deep learning (DL) can extract predictive and prognostic biomarkers from routine pathology slides in colorectal cancer. For example, a DL test for the diagnosis of microsatellite instability (MSI) in CRC has been approved in 2022. Current approaches rely on convolutional neural networks (CNNs). Transformer networks are outperforming CNNs and are replacing them in many applications, but have not been used for biomarker prediction in cancer at a large scale. In addition, most DL approaches have been trained on small patient cohorts, which limits their clinical utility. Methods: In this study, we developed a new fully transformer-based pipeline for end-to-end biomarker prediction from pathology slides. We combine a pre-trained transformer encoder and a transformer network for patch aggregation, capable of yielding single and multi-target prediction at patient level. We train our pipeline on over 9,000 patients from 10 colorectal cancer cohorts. Results: A fully transformer-based approach massively improves the performance, generalizability, data efficiency, and interpretability as compared with current state-of-the-art algorithms. After training on a large multicenter cohort, we achieve a sensitivity of 0.97 with a negative predictive value of 0.99 for MSI prediction on surgical resection specimens. We demonstrate for the first time that resection specimen-only training reaches clinical-grade performance on endoscopic biopsy tissue, solving a long-standing diagnostic problem. Interpretation: A fully transformer-based end-to-end pipeline trained on thousands of pathology slides yields clinical-grade performance for biomarker prediction on surgical resections and biopsies. Our new methods are freely available under an open source license

Clinical-grade Detection of Microsatellite Instability in Colorectal Tumors by Deep Learning

Background and Aims: Microsatellite instability (MSI) and mismatch-repair deficiency (dMMR) in colorectal tumors are used to select treatment for patients. Deep learning can detect MSI and dMMR in tumor samples on routine histology slides faster and cheaper than molecular assays. But clinical application of this technology requires high performance and multisite validation, which have not yet been performed. Methods: We collected hematoxylin and eosin-stained slides, and findings from molecular analyses for MSI and dMMR, from 8836 colorectal tumors (of all stages) included in the MSIDETECT consortium study, from Germany, the Netherlands, the United Kingdom, and the United States. Specimens with dMMR were identified by immunohistochemistry analyses of tissue microarrays for loss of MLH1, MSH2, MSH6, and/or PMS2. Specimens with MSI were identified by genetic analyses. We trained a deep-learning detector to identify samples with MSI from these slides; performance was assessed by cross-validation (n=6406 specimens) and validated in an external cohort (n=771 specimens). Prespecified endpoints were area under the receiver operating characteristic (AUROC) curve and area under the precision-recall curve (AUPRC). Results: The deep-learning detector identified specimens with dMMR or MSI with a mean AUROC curve of 0.92 (lower bound 0.91, upper bound 0.93) and an AUPRC of 0.63 (range, 0.59–0.65), or 67% specificity and 95% sensitivity, in the cross-validation development cohort. In the validation cohort, the classifier identified samples with dMMR with an AUROC curve of 0.95 (range, 0.92–0.96) without image-preprocessing and an AUROC curve of 0.96 (range, 0.93–0.98) after color normalization. Conclusions: We developed a deep-learning system that detects colorectal cancer specimens with dMMR or MSI using hematoxylin and eosin-stained slides; it detected tissues with dMMR with an AUROC of 0.96 in a large, international validation cohort. This system might be used for high-throughput, low-cost evaluation of colorectal tissue specimens

Relationship between the Warburg effect in tumour cells and the tumour microenvironment in colorectal cancer patients:Results from a large multicentre study

Colorectal cancer (CRC) remains one of the most prevalent and deadly cancers worldwide. The tumour-node-metastasis stage (TNM) is currently the most clinically important tool to predict prognosis for CRC patients. However, patients with the same TNM stage can have different prognoses. The metabolic status of tumour cells (Warburg-subtype) has been proposed as potential prognostic factor in CRC. However, potential biological mechanisms underlying the relationship between Warburg-subtype and prognosis have not been investigated in detail. One potential mechanism could be that the metabolic status of tumour cells affects the tumour microenvironment (TME). Our objective was to investigate the relationship between Warburg-subtypes and the TME. Haematoxylin/Eosin stained tumour tissue microarray cores from 2171 CRC patients from the Netherlands Cohort Study were semi quantitatively assessed for tumour infiltrating lymphocytes (TILs) and relative tumour stroma content. 5745 cores were assessed by putting each core in one of four categories for both TILs and stroma. The relationship between Warburg-subtype, TILs, and tumour stroma content was investigated. The frequency of CRC in the different TIL categories was (n, %): very low (2538, 44.2), low (2463, 42.9), high (722, 12.6), and very high (22, 0.4). The frequency of CRC in the different tumour stroma content categories was: = 25% (2755, 47.9), &gt; 25% = 50% (1553, 27) &gt; 50% = 75% (905, 15.8), and &gt; 75% (532, 9.3). There was neither an association between Warburg-subtype and tumour stroma content (p = 0.229) nor between Warburg-subtype and TILs (p = 0.429). This is the first study to investigate the relationship between Warburg-subtypes and the TME in a large population-based series of CRC patients. Our data suggest that the prognostic value of Warburg-subtypes cannot be directly attributed to differences in TILs or tumour stroma content. Our results require confirmation in an independent series

Mitochondrial Dysfunction Inhibits Hypoxia-Induced HIF-1 alpha Stabilization and Expression of Its Downstream Targets

mtDNA variations often result in bioenergetic dysfunction inducing a metabolic switch toward glycolysis resulting in an unbalanced pH homeostasis. In hypoxic cells, expression of the tumor-associated carbonic anhydrase IX (CAIX) is enhanced to maintain cellular pH homeostasis. We hypothesized that cells with a dysfunctional oxidative phosphorylation machinery display elevated CAIX expression levels. Increased glycolysis was observed for cytoplasmic 143B mutant hybrid (m.3243A>G, >94.5%) cells (p 500 mm(3)) took longer for mutant hybrid xenografts, but growth rates were comparable with control tumors upon establishment. Previously, it has been shown that HIF-1 alpha is responsible for tumor establishment. In agreement, we found that HIF-1 alpha expression levels and the pimonidazole-positive hypoxic fraction were reduced for the mutant hybrid xenografts. Our results demonstrate that OXPHOS dysfunction leads to a decreased HIF-1 alpha stabilization and subsequently to a reduced expression of its downstream targets and hypoxic fraction in vivo. In contrast, hypoxia-inducible factor 2-alpha (HIF-2 alpha) expression levels in these xenografts were enhanced. Inhibition of mitochondrial function is therefore an interesting approach to increase therapeutic efficacy in hypoxic tumors

Prognostic and Predictive Value of SARIFA-status Within Molecular Subgroups of Colorectal Cancer:Insights From the Netherlands Cohort Study

We recently proposed Stroma AReactive Invasion Front Areas (SARIFA), defined as direct tumor-adipocyte interaction at the invasion front, as a novel hematoxylin-and-eosin (H&amp;E)-based histopathological? prognostic biomarker in various cancers. Given that microsatellite instability, BRAF, and RAS mutation status are routinely tested? for colorectal cancers (CRC), studying SARIFA's additional prognostic value within these molecular subgroups is crucial. In addition, exploring whether the ?survival benefit from adjuvant therapy differs according to SARIFA-status may enhance patient treatment and outcome. SARIFA-status, BRAF, RAS, and DNA mismatch repair (?MMR) status were available for 1726 CRC patients from the prospective Netherlands Cohort Study (NLCS, 1986-2006). In this study, we investigated (1) the relationship between SARIFA-status and CRC? molecular characteristics, (2) the prognostic value of SARIFA-status within these molecular subgroups, and (3) whether SARIFA-status wa?s associated with survival benefit from adjuvant therapy. SARIFA-positive CRCs more frequently showed a BRAF mutation compared to SARIFA-negative CRCs (P&lt;0.001). BRAF-mutant/MMR-proficient CRCs were enriched in SARIFA-positive cases. SARIFA-positivity was associated with poor CRC-specific (HRrange: 1.47 to 1.78) and overall survival (HRrange: 1.35 to 1.70) within all molecular subgroups except MMR-deficient CRCs. Patients with SARIFA-positive CRC showed a ?CRC-specific survival benefit from adjuvant therapy compared to surgery alone (HRCRC-specific: 0.59; 95% CI: 0.44-0.79), while no CRC-specific survival benefit was observed for patients with SARIFA-negative CRC. To conclude, our results indicate that SARIFA-positivity is more common in the aggressive subset of BRAF-mutant and BRAF-mutant/MMR-proficient CRCs. Moreover?, SARIFA-positivity provides additional prognostic value within molecular subgroups based on BRAF, RAS, and MMR status, suggesting that it may enhance prognostic stratification of CRC patients