Results from the UNITED study: a multicenter study validating the prognostic effect of the tumor–stroma ratio in colon cancer

ESMO Open, Journal Year: 2024, Volume and Issue: 9(4), P. 102988 - 102988

Published: April 1, 2024

•The TSR is a cost-effective and robust histological parameter scored on routine hematoxylin–eosin-stained slides.•This study prospectively validates the independent prognostic effect of for patients with stage II-III colon cancer.•Stroma-high tumors (i.e. intratumoral stromal percentage >50%) significantly lead to worse DFS.•Stroma-high also exhibit chemotherapy resistance, emphasizing clinical need new therapy strategies.•Implementation in international guidelines improved guidance oncological selection envisioned. BackgroundThe TNM (tumor–node–metastasis) Evaluation Committee Union International Cancer Control (UICC) College American Pathologists (CAP) recommended validate tumor–stroma ratio (TSR) as an parameter, since high intratumor percentages have previously predicted poor patient-related outcomes.Patients methodsThe 'Uniform Noting application Tumor-stroma Easy Diagnostic tool' (UNITED) enrolled 27 participating centers 12 countries worldwide. The TSR, categorized stroma-high (>50%) or stroma-low (≤50%), was through standardized microscopic assessment by certified pathologists, disease-free survival (DFS) evaluated 3-year median follow-up. Secondary endpoints were benefit adjuvant (ACT) overall (OS).ResultsA total 1537 included, 1388 eligible II/III curatively operated between 2015 2021. DFS shorter (n = 428) than 960) (3-year rates 70% versus 83%; P < 0.001). In multivariate analysis, remained prognosticator (P 0.001, hazard 1.49, 95% confidence interval 1.17-1.90). As secondary outcome, II III despite treatment 73% 92% 66% 80%; 0.008 0.011, respectively). not receiving ACT 322), outperformed Society Clinical Oncology (ASCO) criteria identifying at risk events (event rate 21% 9%), higher discriminatory (stroma-high 80% ASCO 91%). A trend toward 5-year OS noticeable (74% 83% stroma-low; 0.102).ConclusionThe multicenter UNITED unequivocally prognosticator, confirming outcomes patients. current events, potentially experienced resistance. implementation pathology diagnostics highly aid personalized treatment. outcomes. (OS). 0.102).

Language: Английский

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Self-Supervised Learning Can Distinguish Myelodysplastic Neoplasms from Clinical Mimics Using Bone Marrow Biopsies

medRxiv (Cold Spring Harbor Laboratory), Journal Year: 2025, Volume and Issue: unknown

Published: Feb. 21, 2025

Abstract The diagnosis of myelodysplastic neoplasms (MDS) requires examination the bone marrow for morphologic evidence dysplasia. We sought to determine if a self-supervised learning (SSL) AI image analysis approach may be utilized reliably distinguish MDS from its clinically relevant mimics using biopsies (BMBx). Whole slide images (WSIs) H&E- and reticulin-stained BMBx sections 243 unique patients (89 MDS, 55 non-MDS cytopenic controls [NMCC], 99 negative control [NC] cases) were segmented into tiles analyzed. These then processed Barlow Twins SSL model generate histomorphologic phenotype clusters (HPCs). Review HPCs revealed enriched in captured known histopathologic features including hypercellularity, dysplastic clustered megakaryocytes, increased immature hematopoietic cells, vascularity, fibrosis, cell streaming patterns. Assessment 95 second institution showed consistent HPC enrichment patterns, validating robustness model. trained ensemble slides distinguished NCs with an AUC 0.89, age-matched, NMCCs 0.84. findings demonstrate potential approaches capture diagnostically patterns improve reproducibility diagnosis.

Language: Английский

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The tumour–stroma ratio as predictive aid towards a biopsy‐based treatment strategy in rectal carcinoma

Histopathology, Journal Year: 2025, Volume and Issue: unknown

Published: April 4, 2025

Tumour-stroma ratio (TSR) scores of biopsy material in rectal carcinoma (RC) could aid a biomarker-based, upfront and personalised treatment strategy selection for RC patients. In large retrospective, multicentre cohort, we aimed to validate the predictive value biopsy-scored TSR on neoadjuvant therapy response, secondarily, disease-free overall survival (DFS, OS). Scanned haematoxylin eosin-stained slides were collected from Leiden University Medical Center (N = 116) clinical PROCTOR-SCRIPT 142) RAPIDO 271) trials. was scored per protocol categorised as stroma-low (≤ 50%) or stroma-high (> 50%). Major response defined tumour regression grade (TRG) 1 + 2 by Mandard, including pathological complete response. Ultimately, varied cohort with 373 patients established. Locally advanced more often (P < 0.001). We subsequently observed significantly lower major rates after approach (hazard 0.63, 95% confidence interval 0.41-0.99; P 0.044). Despite correction well-known risk factors Cox hazard analysis, such (y)pTNM substages residual status, had no singular significant influence DFS nor OS multivariate analysis 0.438; 0.934, respectively). Biopsy-scored can predict efficacy, biopsies show less However, patient is multifactorial, although an important predictor, influenced TSR. Scoring reliable histological parameter, implementation which guidelines improve watch-and-wait strategy.

Language: Английский

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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

Diagnostics, Journal Year: 2024, Volume and Issue: 14(8), P. 836 - 836

Published: April 18, 2024

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

Language: Английский

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Whole slide image based prognosis prediction in rectal cancer using unsupervised artificial intelligence

BMC Cancer, Journal Year: 2024, Volume and Issue: 24(1)

Published: Dec. 18, 2024

Rectal cancer is a common worldwide and lacks effective prognostic markers. The development of markers by computational pathology methods has attracted increasing attention. This paper aims to construct signature from whole slide images for predicting progression-free survival (PFS) rectal through an unsupervised artificial intelligence algorithm. A total 238 patients with two datasets were collected the validation signature. tumor detection model was built transfer learning. Then, on basis patches recognized model, convolutional autoencoder decoding into deep latent features. Next, features, divided different clusters. cluster number other hyperparameters optimized nested cross-validation method. percentage each patient's patches, which hereafter called PCF, calculated construction. constructed Cox proportional hazard regression L2 regularization. Finally, bioinformatic analysis performed explore underlying biological mechanisms PCFs. accuracy in distinguishing non-tumor achieved 99.3%. optimal determined be 9. Therfore, 9 PCFs concordance index 0.701 cohort. Kaplan-Meier curves showed had good risk stratification ability. Through analysis, several PCF-associated genes identified. These enriched various gene ontology terms. developed can effectively predict PFS exploration may help promote its clinical translation.

Language: Английский

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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

Published: April 8, 2024

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

Language: Английский

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