Labels

SmartCancer Oncology Knowledge Graph v1.0

The Master Hub for Cancer Types, Biomarkers, Treatments, Resistance, Monitoring and Precision Oncology

Modern oncology is no longer simply about matching a cancer diagnosis with a drug. Cancer treatment increasingly depends on the interaction between cancer type, stage, pathology, molecular biomarkers, immune biology, previous treatment, treatment response and mechanisms of resistance.

The SmartCancer Oncology Knowledge Graph connects those relationships in one continuously expandable framework.

Core SmartCancer model:

CANCER → STAGE → BIOMARKERS → BIOLOGY → TREATMENT → RESPONSE → RESISTANCE → REPROFILING → NEXT STRATEGY

This page is designed to become the central navigation layer for SmartCancer.org's oncology knowledge ecosystem.

What Is the SmartCancer Oncology Knowledge Graph?

A conventional cancer website is usually organized as a collection of articles. A knowledge graph organizes information around entities, relationships and clinical questions.

For example:

EGFR MUTATION
↓
NON-SMALL CELL LUNG CANCER
↓
EGFR-TARGETED THERAPY
↓
TREATMENT RESPONSE
↓
ACQUIRED RESISTANCE
↓
REPEAT MOLECULAR TESTING
↓
NEXT TREATMENT STRATEGY

The same framework can be applied to HER2, KRAS, ALK, BRAF, MSI-H, dMMR, PD-L1, BRCA, HRD, TMB and many other clinically relevant biomarkers.

Important: A biomarker does not automatically mean a patient should receive a particular treatment. Treatment decisions depend on the specific cancer, alteration, stage, prior therapies, clinical evidence, regulatory status, patient factors and the treating oncology team.

How to Use This Master Hub

1. Start With Cancer Type

Choose the cancer or tumor type to explore its staging, pathology, biomarkers and treatment landscape.

2. Explore Biomarkers

Identify molecular, genomic and immune biomarkers that may influence treatment decisions.

3. Explore Treatment

Understand surgery, radiation, chemotherapy, targeted therapy, immunotherapy and newer modalities.

4. Understand Resistance

Explore why cancer may stop responding and how molecular reassessment can influence subsequent treatment.

5. Explore Monitoring

Learn about imaging, tumor markers, liquid biopsy, ctDNA and minimal residual disease testing.

6. Explore Clinical Trials

Connect molecular characteristics and treatment history with investigational approaches.

Oncology Knowledge Graph Architecture

01. Cancer Types

Lung, breast, colorectal, prostate, pancreatic, ovarian, liver, kidney, bladder, brain tumors, melanoma, sarcomas, leukemias, lymphomas and more.

02. Disease State

Localized, locally advanced, metastatic, recurrent, residual, progressive and oligometastatic disease.

03. Biomarkers

Driver mutations, tumor suppressors, DNA repair genes, immune biomarkers and genomic signatures.

04. Treatments

Surgery, radiation, chemotherapy, hormone therapy, targeted therapy, immunotherapy and next-generation therapies.

05. Resistance

Primary resistance, acquired resistance, pathway bypass, target alteration, immune escape and tumor evolution.

06. Monitoring

CT, MRI, PET, pathology, tumor markers, liquid biopsy, ctDNA and MRD.

Master Cancer × Biomarker × Treatment x Resistance Matrix

The central asset of the SmartCancer Knowledge Graph is the relationship between cancer type, biomarker, treatment class and resistance biology.

Cancer Important Biomarker / Feature Potentially Relevant Treatment Class Resistance / Monitoring Concept
Non-small cell lung cancer EGFR EGFR-targeted therapies Acquired resistance; repeat molecular testing; ctDNA
Non-small cell lung cancer ALK ALK inhibitors Secondary resistance mutations; CNS disease; molecular reassessment
Non-small cell lung cancer ROS1 ROS1-targeted therapies Resistance alterations; CNS monitoring
Non-small cell lung cancer KRAS G12C KRAS-directed therapy Adaptive resistance; pathway reactivation
Non-small cell lung cancer BRAF V600E BRAF/MEK-directed therapy MAPK pathway resistance
Non-small cell lung cancer RET fusion RET inhibitors On-target and bypass resistance
Breast cancer HER2 HER2-directed therapy, ADCs Antigen heterogeneity; pathway changes; monitoring
Breast cancer ER/PR Endocrine therapy Endocrine resistance; ESR1 alterations
Breast cancer BRCA1/BRCA2 PARP-directed strategies in appropriate settings DNA-repair restoration and other resistance mechanisms
Colorectal cancer MSI-H / dMMR Immune checkpoint therapy in appropriate settings Primary or acquired immune resistance
Colorectal cancer KRAS / NRAS RAS-directed or pathway-specific strategies depending on alteration MAPK signaling and tumor evolution
Colorectal cancer BRAF V600E BRAF-directed combination strategies MAPK pathway adaptation
Colorectal cancer HER2 HER2-directed therapy in selected patients Target heterogeneity and pathway bypass
Prostate cancer Androgen receptor pathway Androgen-deprivation and androgen-receptor-directed therapies AR amplification, splice variants and lineage adaptation
Prostate cancer BRCA1/2 / HRR PARP-directed therapy in selected settings DNA-repair restoration and clonal evolution
Prostate cancer PSMA PSMA-directed radioligand therapy in appropriate settings Target expression heterogeneity and disease evolution
Melanoma BRAF V600 BRAF/MEK-directed therapy MAPK pathway resistance
Melanoma Immune biomarkers Immune checkpoint therapy Immune escape and tumor microenvironment
Ovarian cancer BRCA / HRD PARP-directed strategies in selected settings Restoration of homologous recombination
Gastric / gastroesophageal cancer HER2 HER2-directed therapy HER2 heterogeneity and acquired resistance
Gastric / gastroesophageal cancer MSI-H / dMMR Immunotherapy in appropriate settings Immune escape
Cholangiocarcinoma FGFR2 alterations FGFR-directed therapy Secondary resistance alterations
Cholangiocarcinoma IDH1 IDH-directed therapy Metabolic and molecular adaptation
Glioma IDH Subtype-specific and investigational targeted approaches Clonal evolution and tumor heterogeneity
Acute myeloid leukemia FLT3 FLT3-directed therapy Clonal evolution and secondary resistance
Acute myeloid leukemia IDH1 / IDH2 IDH-directed therapy Clonal evolution

↔ Swipe the table sideways to see all columns on mobile

Important: This matrix is an educational navigation framework, not a treatment-selection table. Actual treatment depends on the exact cancer subtype, alteration, disease state, prior treatment, regulatory approvals, guidelines and individual patient circumstances.

Biomarker Knowledge Graph

SmartCancer should build dedicated knowledge pages around major biomarker families.

Major Oncogenic Driver Biomarkers

EGFR ALK ROS1 KRAS BRAF RET MET NTRK HER2 FGFR PIK3CA IDH1 IDH2 FLT3 ESR1

DNA Repair and Genomic Biomarkers

BRCA1 BRCA2 HRD MSI-H dMMR TMB POLE PALB2

Immune Biomarkers

PD-L1 PD-1 TMB MSI-H dMMR TILs LAG-3 TIGIT

Major Cancer Treatment Classes

Surgery

Local removal of tumor tissue, lymph-node surgery, cytoreduction and selected metastatic procedures.

Radiation Therapy

External beam radiation, stereotactic techniques, brachytherapy and other localized radiation approaches.

Chemotherapy

Cytotoxic systemic therapy used across numerous cancers and treatment settings.

Hormone Therapy

Endocrine manipulation used particularly in selected breast and prostate cancers.

Targeted Therapy

Therapies directed toward specific molecular alterations or biological pathways.

Immunotherapy

Checkpoint inhibitors, cellular approaches, bispecifics and other immune-directed treatments.

Antibody-Drug Conjugates

Targeting antibodies connected to potent therapeutic payloads.

Bispecific Antibodies

Engineered antibodies capable of engaging two targets simultaneously.

CAR-T / Cellular Therapy

Engineered or selected immune-cell therapies, particularly important in hematologic malignancies.

Radioligand Therapy

Molecular targeting combined with radioactive payloads.

Cancer Vaccines

Personalized and other vaccine approaches designed to stimulate antitumor immunity.

Clinical Trials

Investigational therapies and novel treatment combinations not yet established as standard care.

The Cancer Treatment Resistance Graph

Resistance should be treated as a core component of oncology rather than an afterthought.

TUMOR
↓
TREATMENT PRESSURE
↓
SELECTION OF RESISTANT CELLS
↓
MOLECULAR / CELLULAR ADAPTATION
↓
DISEASE PROGRESSION
↓
REPROFILING
↓
NEW THERAPEUTIC STRATEGY

Major Resistance Categories

  • Primary resistance: inadequate response from treatment initiation.
  • Acquired resistance: progression after an initial response.
  • On-target resistance: alteration of the drug target.
  • Bypass resistance: activation of another pathway.
  • Phenotypic resistance: change in tumor-cell state or lineage.
  • Immune resistance: mechanisms that reduce effective immune attack.
  • Microenvironmental resistance: support from surrounding stromal or immune cells.

Monitoring and Liquid Biopsy Knowledge Graph

Modern oncology increasingly requires measurement of what happens after treatment starts.

Imaging

CT, MRI, PET and other imaging approaches.

Tumor Markers

Blood-based markers that may be useful in selected cancers.

Liquid Biopsy

Analysis of tumor-derived material in blood or other biological fluids.

ctDNA

Circulating tumor DNA can provide molecular information about tumor burden or evolution in selected settings.

MRD

Minimal residual disease testing can detect very small amounts of residual disease in selected cancers.

Repeat Biopsy

Tissue reassessment can sometimes identify new pathology or resistance mechanisms.

Precision Oncology Workflow

DIAGNOSIS
↓
PATHOLOGY
↓
STAGING
↓
MOLECULAR / BIOMARKER TESTING
↓
TREATMENT SELECTION
↓
TREATMENT
↓
RESPONSE ASSESSMENT
↓
SURVEILLANCE
↓
PROGRESSION / RECURRENCE
↓
REPROFILING
↓
NEXT-LINE STRATEGY

Integrated Multi-Modal Oncology

Cancer is a heterogeneous disease. Different patients can have different molecular drivers, immune environments, metastatic patterns and treatment responses even when they share the same cancer diagnosis.

For that reason, modern oncology increasingly uses an integrated multi-modal approach when supported by evidence.

This can involve combinations of:

  • Surgery
  • Radiation
  • Chemotherapy
  • Targeted therapy
  • Immunotherapy
  • Hormone therapy
  • ADCs
  • Cellular therapy
  • Radiopharmaceutical therapy
  • Clinical trials
  • Supportive and palliative care

Systems principle: A systems-level cancer problem requires systems-level thinking. But integrated care must remain evidence-based. Combining multiple interventions simply because they are individually interesting is not equivalent to a clinically validated combination.

Major Cancer Knowledge Hubs

Lung Cancer

NSCLC, SCLC, EGFR, ALK, ROS1, KRAS, BRAF, RET, MET, HER2, NTRK, immunotherapy and resistance.

Breast Cancer

ER, PR, HER2, BRCA, HRD, ESR1, endocrine therapy, targeted therapy and ADCs.

Colorectal Cancer

KRAS, NRAS, BRAF, MSI-H, dMMR, HER2, EGFR, immunotherapy and ctDNA.

Prostate Cancer

Androgen receptor signaling, BRCA, HRR, PSMA, PARP strategies and radioligand therapy.

Pancreatic Cancer

KRAS, DNA repair, molecular subtypes, immunotherapy and emerging treatment strategies.

Ovarian Cancer

BRCA, HRD, PARP strategies, antibody-drug conjugates and immunotherapy.

Melanoma

BRAF, immune checkpoint therapy, targeted therapy and immune resistance.

Hematologic Cancers

Leukemias, lymphomas and myeloma, including CAR-T, bispecific antibodies and targeted therapies.

SmartCancer Knowledge Graph: Priority Page Architecture

The master hub should ultimately connect to a large network of supporting pages.

Tier 1 — Master Pillars

Tier 2 — Biomarker Hubs

Tier 3 — Treatment Hubs

SmartCancer Oncology Explorer — Future Interactive Tool

The next development stage should convert this knowledge graph into an interactive educational explorer.

Potential User Interface

Step 1: Select cancer type.

Step 2: Select stage or disease state.

Step 3: Select known biomarkers.

Step 4: Select previous treatment.

Step 5: Select response status.

Output: educational information about relevant treatment classes, biomarkers, resistance mechanisms, monitoring approaches and clinical-trial categories.

This tool should never present itself as an automated oncologist or make individualized treatment recommendations.

Evidence Framework

SmartCancer should clearly distinguish established treatments from emerging science.

E0 — Hypothesis

Theoretical mechanism or research concept.

E1 — Preclinical

Cellular, animal or laboratory evidence.

E2 — Early Clinical

Early human studies or preliminary clinical evidence.

E3 — Comparative Evidence

Meaningful controlled or comparative clinical evidence.

E4 — Established Evidence

Substantial evidence supporting defined clinical use.

E5 — Standard / Guideline-Supported

Established treatment supported by authoritative clinical guidance.

What Makes the SmartCancer Knowledge Graph Different?

  • Patient-first: Organized around questions patients actually ask.
  • Biology-first: Connects cancer diagnosis to molecular and immune biology.
  • Resistance-aware: Treatment failure is part of the model.
  • Evidence-aware: Emerging science is separated from established care.
  • Multi-modal: Does not reduce oncology to a single treatment class.
  • Continuously expandable: New biomarkers and treatments can be added without rebuilding the architecture.
  • AI-ready: Structured relationships can eventually support AI-assisted search and navigation.

SmartCancer Oncology Knowledge Graph v1.0 — The Core Map

CANCER TYPE
↓
HISTOLOGY + STAGE
↓
BIOMARKERS
↓
TUMOR BIOLOGY
↓
TREATMENT OPTIONS
↓
COMBINATION STRATEGIES
↓
RESPONSE MONITORING
↓
RESISTANCE
↓
REPROFILING
↓
NEXT-LINE TREATMENT
↓
CLINICAL TRIALS
↓
LONGITUDINAL CANCER MANAGEMENT

Frequently Asked Questions

What is a cancer knowledge graph?

A cancer knowledge graph is a structured system that connects cancer types, biomarkers, treatments, resistance mechanisms, monitoring technologies and clinical trials rather than presenting them as isolated topics.

What is the Cancer × Biomarker × Treatment Matrix?

It is a framework connecting specific cancers with clinically relevant biomarkers and the treatment classes that may be relevant to those biological characteristics, while also showing important resistance and monitoring concepts.

Does having a biomarker mean a patient can receive a targeted drug?

Not necessarily. Biomarker interpretation depends on the exact alteration, cancer type, clinical context, treatment approval, evidence and patient circumstances.

Why is resistance included in the knowledge graph?

Because cancer can evolve under treatment pressure. Understanding resistance is essential for understanding why treatment can stop working and why additional testing may sometimes be considered.

What is precision oncology?

Precision oncology uses information about the cancer's molecular and biological characteristics, together with clinical factors, to help inform treatment decisions.

What is integrated multi-modal oncology?

It is an approach that considers multiple appropriate treatment modalities, such as surgery, radiation, systemic therapy, targeted therapy and immunotherapy, when evidence and the clinical situation support their use.

Will SmartCancer provide individualized treatment recommendations?

The SmartCancer Knowledge Graph is intended as an educational and navigation resource. It should not replace individualized assessment by qualified oncology professionals.

Editorial and Medical Standards

SmartCancer should maintain a strict distinction between:

  • Approved or guideline-supported treatment.
  • Established clinical evidence.
  • Emerging clinical evidence.
  • Early clinical research.
  • Preclinical evidence.
  • Mechanistic hypotheses.
  • Patient anecdotes and testimonials.

Mechanistic plausibility, laboratory results or anecdotal reports should never be presented as equivalent to randomized clinical evidence or established standards of care.

Medical disclaimer: This page is for educational purposes only. It does not diagnose cancer, recommend an individualized treatment, or replace professional medical advice. Cancer treatment decisions should be made with qualified healthcare professionals based on the individual's diagnosis, pathology, staging, biomarker results, medical history and treatment goals.

Conclusion

The SmartCancer Oncology Knowledge Graph is designed to become more than an article.

It is the proposed information architecture for SmartCancer.org's entire oncology ecosystem.

Its central idea is simple:

Don't look at cancer treatment as a list of drugs.

Look at it as a connected system of
CANCER + BIOLOGY + BIOMARKERS + TREATMENT + RESPONSE + RESISTANCE + ADAPTATION.

As oncology advances, the most useful cancer-information platform will not simply tell readers what a treatment is. It will help them understand where that treatment fits in the larger biological and clinical map of cancer.

That is the purpose of the SmartCancer Oncology Knowledge Graph.

Version 1.0 is the foundation. Future versions can expand this framework into an interactive oncology explorer connecting hundreds of cancer entities, biomarkers, treatments, resistance mechanisms, diagnostic technologies and clinical trials.

SmartCancer Oncology Knowledge Graph v1.0
Master Oncology Hub • Cancer × Biomarker × Treatment Architecture • Educational Resource

Labels:

Comments

Post a Comment

Popular Posts