Predictive model for lymph node metastasis of colorectal cancer - using PET / CT
Ontology highlight
ABSTRACT:
DISEASE(S): Colorectal Cancer
PROVIDER: 2644734 | ecrin-mdr-crc |
REPOSITORIES: ECRIN MDR
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Project description:Primary outcome(s): Diagnostic ability (sensitivity, specificity, accuracy, positive predictive value, negative predictive value, and area under the curve) for lymph node metastasis
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Project description:To describe the accuracy of FAPI PET/CT in the detection of regional lymph node metastases in patients with colorectal cancer in comparison with standard diagnostic imaging and (in operated patients) histopathology, aiming to provide early evidence of the diagnostic value of FAPI PET/CT.
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Project description:Expression profiling of breast cancer tumours, comparing 10 year survivors to deceased patients Background It is of great significance to find better markers to correctly distinguish between high-risk and low-risk breast cancer patients since the majority of breast cancer cases are at present being overtreated. Methods 46 tumours from node-negative breast cancer patients were studied with gene expression microarrays. A t-test was carried out in order to find a set of genes where the expression might predict clinical outcome. Two classifiers were used to evaluate the gene lists on the different data sets, a correlation-based classifier and a VFI (Voting Features Interval) classifier. We then evaluated the predictive accuracy of this expression signature on tumour sets from two similar studies on lymph-node negative patients which had developed gene expression signatures superior to current methods in classifying node-negative breast tumours. These two signatures were also tested on our material. Results A list of 51 genes whose expression profiles could predict clinical outcome with high accuracy in our material (96% or 89% accuracy in cross-validation, depending on type of classifier) was developed. When tested on two independent data sets, the expression signature based on the 51 identified genes had good predictive qualities in one of the data sets (74% accuracy), whereas their predictive value on the other data set were poor, presumably due to the fact that only 23 of the 51 genes were found in that material. We also found that previously developed expression signatures could predict clinical outcome well to moderately well in our material (72% and 61%, respectively). Conclusion The list of 51 genes derived in this study might have potential for clinical utility as a prognostic gene set, and may include candidate genes of potential relevance for clinical outcome in breast cancer. According to the predictions by this expression signature, 30 of the 46 patients should have had different adjuvant treatment than they did. Keywords: Expression Microarray, Lymph-node-negative Breast Cancer, Clinical Outcome, Classification
2008-08-29 | GSE12071 | GEO
Project description:Primary outcome(s): Diagnostic ability (sensitivity, specificity, accuracy, positive predictive value, and negative predictive value) for lymph node metastasis
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Project description:Using a mouse model of breast cancer that develops spontaneous lymph node metastasis, we performed high-resolution single-cell RNA sequencing (scRNA-Seq) of the primary tumor and TDLN to measure how cancer cells adapt to the dynamic lymph node microenvironment. To understand the dynamic change of lymph node microenvironment after cancer cell invasion, we also compared the gene-expression alteration between naive lymph node and TDLN at single-cell level.
2023-06-14 | GSE168181 | GEO
Project description:Understanding the molecular mechanisms and gene expression in laryngeal squamous cell carcinoma (LSCC) may explain its aggressive biological behavior and regional metastasis pathways. Better understanding of the molecular mechanisms underlying LSCC metastasis and the search for possible molecular targets seems promising. Interpreting the links between the differentially expressed genes in advanced stages can lead to a search for predictive markers that can also help determine the possible treatment routes. We designed this study to detect possible genetic alterations in a homogeneous group of patients with locoregionally advanced laryngeal cancer who underwent total laryngectomy and neck dissection. Patients with and without lymph node metastasis were selected to examine the differential gene expression in the normal mucosa, tumor, and lymph node tissues of each patient. Our main purpose was to identify the possible commonly expressed genes in this homogenous group of Turkish patients with locoregionally advanced laryngeal cancer. Second, we aimed to determine the predictive role of these genes in lymph node metastasis and overall prognosis.
2022-10-07 | GSE201777 | GEO
Project description:Expression profiling of breast cancer tumours, comparing 10 year survivors to deceased patients Background It is of great significance to find better markers to correctly distinguish between high-risk and low-risk breast cancer patients since the majority of breast cancer cases are at present being overtreated. Methods 46 tumours from node-negative breast cancer patients were studied with gene expression microarrays. A t-test was carried out in order to find a set of genes where the expression might predict clinical outcome. Two classifiers were used to evaluate the gene lists on the different data sets, a correlation-based classifier and a VFI (Voting Features Interval) classifier. We then evaluated the predictive accuracy of this expression signature on tumour sets from two similar studies on lymph-node negative patients which had developed gene expression signatures superior to current methods in classifying node-negative breast tumours. These two signatures were also tested on our material. Results A list of 51 genes whose expression profiles could predict clinical outcome with high accuracy in our material (96% or 89% accuracy in cross-validation, depending on type of classifier) was developed. When tested on two independent data sets, the expression signature based on the 51 identified genes had good predictive qualities in one of the data sets (74% accuracy), whereas their predictive value on the other data set were poor, presumably due to the fact that only 23 of the 51 genes were found in that material. We also found that previously developed expression signatures could predict clinical outcome well to moderately well in our material (72% and 61%, respectively). Conclusion The list of 51 genes derived in this study might have potential for clinical utility as a prognostic gene set, and may include candidate genes of potential relevance for clinical outcome in breast cancer. According to the predictions by this expression signature, 30 of the 46 patients should have had different adjuvant treatment than they did. Keywords: Expression Microarray, Lymph-node-negative Breast Cancer, Clinical Outcome, Classification 23 fresh frozen primary node negative breast cancer tumours from 10 year survivors were compared to 23 tumours from deceased patients in order to find genes where the expression differed between the two groups Microarrays were produced at the Swegene DNA Microarray Resource Center, Department of Oncology, Lund University, Sweden (http://swegene.onk.lu.se). Frozen tumours were homogenized together with TRIzol Reagent (Invitrogen, Carlsbad, CA, USA). From the cell-suspension total RNA was extracted using RNeasy mini kit (Qiagen, Valencia, CA, USA) according to the manufacturer’s protocol. The quality of the RNA was evaluated with the Agilent 2100 BioAnalyser (Agilent Technologies, Palo Alto, CA, USA). Specimens where the 28S/16S ratio was lower than 1.0 or the RIN-value was lower than 6.7 were excluded from the study. For each sample, Cy3-dCTP (Amersham Biosciences, Buckinghamshire, UK) labelled probes were synthesized from 5 µg of the total tumour RNA and Cy5-dCTP (Amersham Biosciences) labelled reference were synthesized from 5 µg of commercial reference RNA (Universal Human Reference RNA, Stratagene, La Jolla, CA, USA) by reverse transcription. The probes were purified using ChipShot™ labelling cleanup system (Promega, Madison, WI, USA). The hybridizations were carried out using Pronto! Micro Array reagent systems (Corning Inc., Corning, NY, USA). For each sample, labelled tumour cDNA and reference cDNA were co-precipitated and hybridised to the microarray slide. The microarray slides were scanned with Agilent microarray scanner G2565AA (Agilent Technologies) and image analysis was performed using the Genepix 6.0.0.45 software (Axon Instruments, Union City, CA, USA).
2008-08-29 | E-GEOD-12071 | biostudies-arrayexpress
Project description:If we can more accurately predict the likelihood of regional lymph node metastasis (LNM) for endoscopically resected T1-stage colorectal cancers (CRC), the number of unnecessary additional surgeries can be reduced. We aimed of identify miRNA markers that can predict LNM-positive tumors among T1-stage CRCs and we also developed a miRNA classifier set for facilitating the accuracy and applicability.
2015-09-30 | GSE70574 | GEO
Project description:PURPOSE:The aim of this study was to determine the prognostic significance of PET/CT findings in women with cervical cancer and describe the normalization of lymph node SUVmax (nSUVmax). MATERIALS AND METHODS:A retrospective review was performed of 113 patients with cervical cancer who underwent a PET/CT before receiving definitive therapy. SUVmax measurements were normalized to the SUV of the pelvic blood pool. Patient, tumor, and PET/CT data were correlated to extracervical recurrence-free survival (ecRFS) and lymph node pathology. RESULTS:Of 113 patients, there were 23 (20%) extracervical recurrences. On univariate analysis, stage, histology, nSUVmax, and radiographic size of the primary tumor, and nSUVmax of the most hypermetabolic lymph node were significantly associated with ecRFS. On multivariable analysis, nSUVmax and radiographic size of the primary tumor remained associated with ecRFS (both P < 0.001). Sixty-six patients underwent pelvic, common iliac, and/or para-aortic nodal sampling. The sensitivity, specificity, false-negative, and false-positive rates of PET/CT for lymph node metastases were 53%, 75%, 6%, and 82%, respectively. On univariate analysis, nSUVmax, and radiographic size of the primary tumor, and nSUVmax of the most hypermetabolic lymph node, and radiographic size of the largest lymph node, were associated with the presence of at least one pathologically positive lymph node. On multivariable analysis, only the radiographic size of the largest lymph node remained significantly associated with lymph node metastases (P < 0.001). CONCLUSIONS:The size and nSUVmax of the primary tumor were associated with ecRFS. PET/CT has a low false-negative rate but high false-positive rate for lymph node metastases.
| S-EPMC7456572 | biostudies-literature