Novel Internationally Verified Method Reports Desmoplastic Reaction as the Most Significant Prognostic Feature For Disease-specific Survival in Stage II Colorectal Cancer

Background. Evaluation of lymph node status is critical in colorectal carcinoma (CRC) treatment. However, as patients with node involvement may be incorrectly classified into earlier stages if the examined lymph node (ELN) number is too small and escape adjuvant therapy, especially for stage II CRC. The aims of this study were to assess the impact of the ELN on the survival of patients with stage II colorectal cancer and to determine the optimal number. Methods. Data from the US Surveillance, Epidemiology, and End Results (SEER) database on stage II resected CRC (1988-2013) were extracted for mathematical modeling as ELN was available since 1988. Relationship between ELN count and stage migration and disease-specific survival was analyzed by using multivariable models. The series of the mean positive LNs, odds ratios (ORs), and hazard ratios (HRs) were fitted with a LOWESS (Locally Weighted Scatterplot Smoothing) smoother, and the structural break points were determined by the Chow test. An independent cohort of cases from 2014 was retrieved for validation in 5-year disease-specific survival (DSS). Results. An increased ELN count was associated with a higher possibility of metastasis LN detection (OR 1.010, CI 1.009-1.011, p<0.001) and better DSS in LN negative patients (OR 0.976, CI 0.975-0.977, p<0.001). The cut-off point analysis showed a threshold ELN count of 21 nodes (HR 0.692, CI 0.667-0.719, p<0.001) and was validated with significantly better DSS in the SEER 2009 cohort CRC (OR 0.657, CI 0.522-0.827, p<0.001). The cut-off value of the ELN count in site-specific surgeries was analyzed as 20 nodes in the right hemicolectomy (HR 0.674, CI 0.638-0.713, p<0.001), 19 nodes in left hemicolectomy (HR 0.691, CI 0.639-0.749, p<0.001), and 20 nodes in rectal resection patients (HR 0.671, CI 0.604-0.746, p<0.001), respectively. Conclusions. A higher number of ELNs are associated with more-accurate node staging and better prognosis in stage II CRCs. We recommend that at least 21 lymph nodes be examined for accurate diagnosis of stage II colorectal cancer.

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A Multicenter Study of the Prognostic Value of Desmoplastic Reaction Categorization in Stage II Colorectal Cancer

The American Journal of Surgical Pathology ◽

10.1097/pas.0000000000001272 ◽

2019 ◽

Vol 43 (8) ◽

pp. 1015-1022 ◽

Cited By ~ 1

Author(s):

Hideki Ueno ◽

Yukihide Kanemitsu ◽

Shigeki Sekine ◽

Megumi Ishiguro ◽

Eisaku Ito ◽

...

Keyword(s):

Colorectal Cancer ◽

Multicenter Study ◽

Prognostic Value ◽

Stage Ii ◽

Desmoplastic Reaction ◽

Stage Ii Colorectal Cancer

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Abstract 2096: A deep learning system to predict disease-specific survival in stage II and stage III colorectal cancer

10.1158/1538-7445.am2020-2096 ◽

2020 ◽

Author(s):

Ellery Wulczyn ◽

David F. Steiner ◽

Melissa Moran ◽

Markus Plass ◽

Robert Reihs ◽

...

Keyword(s):

Colorectal Cancer ◽

Deep Learning ◽

Learning System ◽

Stage Ii ◽

Stage Iii ◽

Disease Specific Survival ◽

Disease Specific

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High Tumour Cannabinoid CB1 Receptor Immunoreactivity Negatively Impacts Disease-Specific Survival in Stage II Microsatellite Stable Colorectal Cancer

PLoS ONE ◽

10.1371/journal.pone.0023003 ◽

2011 ◽

Vol 6 (8) ◽

pp. e23003 ◽

Cited By ~ 29

Author(s):

Sofia B. Gustafsson ◽

Richard Palmqvist ◽

Maria L. Henriksson ◽

Anna M. Dahlin ◽

Sofia Edin ◽

...

Keyword(s):

Colorectal Cancer ◽

Cb1 Receptor ◽

Stage Ii ◽

Disease Specific Survival ◽

Cannabinoid Cb1 Receptor ◽

Disease Specific

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A genetic signature of relapse in stage II colorectal cancer derived from formalin fixed paraffin embedded tissue (FFPE) tissue using a unique disease specific colorectal array

Journal of Clinical Oncology ◽

10.1200/jco.2006.24.18_suppl.3519 ◽

2006 ◽

Vol 24 (18_suppl) ◽

pp. 3519-3519 ◽

Cited By ~ 3

Author(s):

P. G. Johnston ◽

K. Mulligan ◽

E. Kay ◽

J. Black ◽

S. Moore ◽

...

Keyword(s):

Colorectal Cancer ◽

Gene Signature ◽

Ffpe Tissue ◽

Stage Ii ◽

Cancer Disease ◽

Formalin Fixed Paraffin ◽

Formalin Fixed Paraffin Embedded ◽

Ffpe Tissues ◽

Stage Ii Colorectal Cancer ◽

Disease Specific

3519 Background: We have developed the first disease specific microarray for colorectal cancer using a transcriptome-based approach. This unique tool has been specially designed and optimised for analysis of gene expression profiles from formalin fixed paraffin embedded tissues (FFPE). To evaluate this tool we are conducting a study in patients with Dukes B (stage II) colorectal cancer (CRC) using FFPE tissues to determine a prognostic genetic signature predicting disease recurrence. Methods: The colorectal array was developed using a high-throughput transcriptome-based approach and encodes over 52,500 transcripts expressed in normal and diseased colorectal tissue. To date, tumours from 32 patients have been selected (mean FFPE tissue block age - 10.4 years) from the stage II CRC cohort of a phase III randomized trial comparing 5-FU/Leucovorin versus no adjuvant treatment (NI240). The patients were from the observation alone arm;19 of whom were disease-free for 5 years post-randomisation, while 13 suffered relapse prior to 3 years. Results: RNA was extracted from all 32 FFPE tissue samples, amplified, labelled and hybridised to the colorectal cancer disease specific array. Raw data was normalised using scalar, median-polish and z-score strategies and scalar was selected as the best strategy in relation to predictive error. Within this data set genes selected by correlation using ANOVA performed best in both KNN and support vector machine algorithms (supervised). Using this approach a gene signature containing 48 genes demonstrated 100% accuracy in the prediction of relapse in stage II CRC (p<0.001). This signature was also able to separate samples at the meta-node level using unsupervised hierarchical clustering. Conclusion: We have developed the first colorectal cancer disease specific microarray and demonstrated its use using FFPE tissues. Using this approach we have derived a gene signature that predicts for a high likelihood of early relapse in stage II CRC. [Table: see text]

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Prognosis Prediction for Stage II Colorectal Cancer by Fusing CT Radiomics and Deep Learning Features of Primary Lesion and Peripheral Lymph Nodes

SSRN Electronic Journal ◽

10.2139/ssrn.3736713 ◽

2020 ◽

Author(s):

Menglei Li ◽

Jing Gong ◽

Yichao Bao ◽

Dan Huang ◽

Junjie Peng ◽

...

Keyword(s):

Colorectal Cancer ◽

Deep Learning ◽

Lymph Nodes ◽

Primary Lesion ◽

Stage Ii ◽

Prognosis Prediction ◽

Peripheral Lymph ◽

Stage Ii Colorectal Cancer ◽

Deep Learning Features

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Transcriptome of Tumor-Infiltrating T Cells in Colorectal Cancer Patients Uncovered a Unique Gene Signature in CD4+ T Cells Associated with Poor Disease-Specific Survival

Vaccines ◽

10.3390/vaccines9040334 ◽

2021 ◽

Vol 9 (4) ◽

pp. 334

Author(s):

Salman M. Toor ◽

Varun Sasidharan Nair ◽

Reem Saleh ◽

Rowaida Z. Taha ◽

Khaled Murshed ◽

...

Keyword(s):

Colorectal Cancer ◽

T Cells ◽

T Cell Activation ◽

Cd4 T Cells ◽

Poor Prognosis ◽

Gene Signature ◽

The Cancer Genome Atlas ◽

Disease Specific Survival ◽

Unique Gene ◽

Disease Specific

Colorectal cancer (CRC) is influenced by infiltration of immune cell populations in the tumor microenvironment. While elevated levels of cytotoxic T cells are associated with improved prognosis, limited studies have reported associations between CD4+ T cells and disease outcomes. We recently performed transcriptomic profiling and comparative analyses of sorted CD4+ and CD8+ tumor-infiltrating lymphocytes (TILs) from bulk tumors of CRC patients with varying disease stages. In this study, we compared the transcriptomes of CD4+ with CD8+ TILs. Functional annotation pathway analyses revealed the downregulation of inflammatory response-related genes, while T cell activation and angiogenesis-related genes were upregulated in CD4+ TILs. The top 200 deregulated genes in CD4+ TILs were aligned with the cancer genome atlas (TCGA) CRC dataset to identify a unique gene signature associated with poor prognosis. Moreover, 69 upregulated and 20 downregulated genes showed similar trends of up/downregulation in the TCGA dataset and were used to calculate “poor prognosis score” (ppScore), which was significantly associated with disease-specific survival. High ppScore patients showed lower expression of Treg-, Th1-, and Th17-related genes, and higher expression of Th2-related genes. Our data highlight the significance of T cells within the TME and identify a unique candidate prognostic gene signature for CD4+ TILs in CRC patients.

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