Colorectal Cancer Patient Data on Malnutrition, Immunity, and Tumor Microbiota
by Federica Perillo·Updated 11d ago
19.0 KB1files
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Description
A prospective pilot study of 43 colorectal cancer patients from July 2017 to August 2021, evaluating preoperative nutritional status, intratumoral immune phenotypes, and tumor-associated microbiota. The dataset, authored by Federica Perillo and shared under a CC-BY-4.0 license, includes biochemical, anthropometric, and nutritional profiles, with microbiota analysis performed on a subset of 8 patients.
Use Cases
Investigating associations between malnutrition screening scores and altered T cell phenotypes based on immune profiling data.
Analyzing links between neutrophil lymphocyte ratio (NLR) and specific bacterial genera like Bacteroides and Prevotella mentioned in the results.
Modeling the relationship between preoperative nutritional status and tissue-infiltrating neutrophil levels in colorectal cancer patients.
Exploring potential biomarkers for suppressed anti-tumor immunity based on combined nutritional and microbiota profiles.
Strengths
Prospective study design with 43 enrolled patients provides a structured clinical cohort.
Multimodal data includes biochemical, anthropometric, nutritional, immune phenotype, and microbiota analysis.
Specific time range from July 2017 to August 2021 defines the study period.
Limitations
Row count is unknown, which may limit suitability assessment.
Column-level documentation is absent; field semantics must be inferred after download.
Microbiota analysis was performed on a small subset of only 8 patients.
Provenance
Source
figshare, author Federica Perillo.
Collection Method
Prospective clinical study at IRCCS Ca′ Granda Ospedale Maggiore Policlinico in Milan.
Time Range
July 2017 to August 2021
Freshness
Last updated 2026-05-28 15:37:38; freshness should be verified.
Geography
Milan, Italy (inferred from hospital location).
The primary data file is a 19.0 KB DOCX document, which is a very small size and likely contains summarized results rather than raw tabular data.