Francesco Iorio

CRISPR-VUS identifies rare variants linked to gene dependency in cancer cell lines, prioritizing potential drivers and therapeutic targets through functional validation.

This paper develops GepiClock, an epigenetic clock for cancer cells, revealing age-related therapeutic vulnerabilities in cancer cell lines.

This study shows that LSD induces gene expression patterns opposing aging and neurodegeneration in the brain, suggesting potential therapeutic effects through transcriptional reversal.

The paper identifies ADD3 as a regulator of glioblastoma stem cell morphology and tumor-tumor connections, showing its role in proliferation and survival.

The paper trains an ensemble classifier to predict cetuximab sensitivity in colorectal cancer PDXs using multi-omic data, achieving high accuracy and demonstrating its utility for therapeutic biomarker development.

This study benchmarks seven computational methods for correcting CN and proximity biases in CRISPR-Cas9 screens, finding AC-Chronos and CRISPRcleanR perform best in different scenarios.

The paper provides a dataset and R package to benchmark CRISPR-Cas9 screening pipelines using HT-29 cells and a commercial guide RNA library.

CRISPRcleanRWebApp is a web tool that processes CRISPR-Cas9 viability screens to reduce false positives by correcting biases in gene targeting.

The paper develops a computational framework to create reduced gene templates for supervised analysis of scale-limited CRISPR-Cas9 screens, improving efficiency without compromising results.

CoRe identifies core-fitness genes from CRISPR-Cas9 screens, outperforming existing tools and providing more reliable results.

The paper integrates two large CRISPR-Cas9 screens to improve the detection of gene dependencies and cancer vulnerabilities by addressing biases and batch effects.

The paper designs a smaller genome-wide CRISPR-Cas9 library with reduced size while maintaining sensitivity and specificity, enhancing its applicability in complex models.

The paper identifies LRRK2-regulated pathways for extracellular tau uptake in human neurons using CRISPR screens, showing LRRK2's role in monomeric tau endocytosis.

This study integrates drug sensitivity data with CRISPR screens to identify drug mechanisms and biomarkers for cancer therapy.

CELLector selects relevant cancer cell lines based on patient genomic data to improve in vitro model relevance and bridge cell line screens to primary tumor sub-cohorts.

JACKS improves hit identification in CRISPR/Cas9 screens by jointly analyzing data from the same guide RNA library, reducing required cell numbers by 2.5-fold.

The paper shows that targeting tandem amplified regions in CRISPR-Cas9 screens reduces cellular fitness, while chromosomal duplications have minimal effects.

CRISPRcleanR reduces false positives in CRISPR-Cas9 screens by correcting gene-independent responses without assuming copy number status.

The paper develops SLAPenrich to analyze pathway alterations in cancer hallmarks across 4,415 patients, revealing hallmark predominance and suggesting novel driver genes.

CellMinerCDB integrates pharmacogenomic data from multiple cancer cell line databases to identify drug response determinants, reproducibility, and novel genomic signatures.

This paper describes a method to identify drug resistance mutations in cancer using genome-wide chemical mutagenesis and next-generation sequencing, enabling the discovery of both known and novel resistance mechanisms.

The paper introduces BiRewire 3, a tool for efficiently randomizing biological networks while preserving node functional characteristics, and demonstrates its application in network analysis.

The paper introduces LOBICO, a logic modeling approach for binary inputs predicting continuous outputs, showing it outperforms single-gene predictors in cancer drug response.