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From your first question to
published research.

Our members don't just read about cancer research — they do it. Through three programs and a growing set of active projects, students run real computational and translational oncology work with mentor guidance, aiming for conference presentations and publication.

01

One-on-One Mentorship

Work with a current computational-biology student researcher to learn a topic you care about, then get guided through cold-emailing and connecting with a professor or physician willing to mentor you.

Open · newcomers
02

Cold-Emailing Assistance 101

For students with a unique oncology research question. We reach out to hundreds of faculty and physicians who may mentor student researchers — and guarantee certified mentorship within two months of registration.

Open · year-round
03

CRS AACR Research Team

Our selected team is conducting drug-discovery research with plans to present at the AACR 2027 Annual Conference in Orlando. Applications for the AACR 2028 team open in April 2027.

Currently full
Active Research

Real projects, right now.

Three questions nobody had answered for our members — so they started answering them.

Computational · Structure-Based Drug Discovery

DCLK1 Virtual Screening

DCLK1 is a kinase implicated in colorectal and pancreatic cancer. Our AACR team screened 3,000+ compounds against it using molecular docking (idock / AutoDock Vina) and ChimeraX structural analysis, anchored on PDB structures 7F3G and 2HYY. The most promising hits are now being validated through laboratory testing — microscale thermophoresis (MST), isothermal titration calorimetry (ITC), and kinase-array assays — with the goal of presenting at AACR 2027.

idock · AutoDock VinaChimeraXPDB 7F3G · 2HYYMST · ITC · kinase arrays
3000COMPOUNDS SCREENED
DETECTING MOTT CELLS
Deep Learning · Digital Pathology

Neural Networks for Multiple Myeloma

In multiple myeloma, ER stress from protein misfolding drives immunoglobulin buildup that forms Russell bodies — the morphological signature of Mott cells. Member researcher Austin is investigating whether a neural network can detect these cells directly from pathology slides. It's a genuinely open problem: no published model targets them, and no public dataset labels them — which is exactly what makes it worth doing.

Neural networksDigital pathologyMultiple myelomaMott cells · Russell bodies
Microbiome · Colorectal Cancer

Fusobacterium nucleatum & Colorectal Cancer

Member researcher Alex is investigating Fusobacterium nucleatum, an oral bacterium repeatedly found enriched in colorectal tumor tissue. The project asks how it reaches the tumor, what it does to the tumor microenvironment, and what that means for treatment response — connecting the microbiome to one of the most common cancers worldwide.

Tumor microbiomeColorectal cancerTumor microenvironment
TUMOR MICROBIOME
More Active Projects

Led by our members & leadership.

Computational · Drug Repurposing

EGFR L858R Repurposing

A drug-repurposing pipeline against the EGFR L858R lung-cancer mutation using AutoDock Vina and Boltz-2 structure prediction, developed with faculty mentorship.

Machine Learning · Selective Binders

PGK2 Selective-Binder ML

A machine-learning effort to predict small molecules that selectively bind PGK2 over its near-identical isoform, combining DNA-encoded library signal with structure-based modeling at a Baylor drug-discovery lab.

Digital Pathology · Concordance

FOLR1 IHC Concordance

A pathology study at MD Anderson comparing analog vs. digital scoring of FOLR1 immunohistochemistry across biopsy and resection specimens, targeting AACR and ASCO GU.

Hands-On Labs

Two labs. Real specimens.

Fall · Pathology Analysis

100+ tissue slides

Members work through 100+ tissue slides, learning to identify the cellular characteristics that distinguish healthy tissue from cancer — guided and hands-on.

Spring · Bacterial Transformation

Immunology & viruses

A transformation lab anchoring a deeper unit on immunology and viruses, connecting molecular techniques to how the body fights cancer.

Have a question worth answering?

Register, apply, and we'll match you with the right program, mentor, and dataset.