NSCLC EGFR-TKI Resistance Pathway Mapping

Oncology

NSCLC EGFR-TKI Resistance Pathway Mapping

Oncology unit needed resistance mechanism targets for osimertinib-progressed patients to design combination strategy before Phase 1b trial protocol lock.

Company

Top-20 pharma oncology discovery unit

Timeline

July to August 2025

Engagement

Resistance Pathway Mapping Pipeline

Resistance Pathway Mapping

3 wks: Computational delivery
634: Resistance-associated nodes
8: Combination targets + dossiers
3: Novel bypass pathways identified

The Challenge

An oncology discovery unit's osimertinib combination program had stalled after Phase 1a showed limited durability in EGFR-mutant NSCLC patients with acquired resistance. Internal transcriptomic analysis of 48 post-progression biopsies identified MET amplification in 22% of cases but left 78% of resistance unexplained. Protocol lock for Phase 1b was 5 weeks away. Leadership needed a ranked resistance target list with pathway context, combination rationale, and biomarker stratification hypotheses.

Business Constraints

Budget: $210K (combination strategy budget)
Timeline: Ranked dossiers in 3 weeks, biomarker appendix in week 4
Must integrate client proprietary post-progression biopsy RNA-seq (n=48)
Deliverables must support Phase 1b protocol biomarker section

TargetIQ Approach

Week 1: Resistance Signature Discovery and Pathway Reconstruction

Input

Client proprietary post-osimertinib biopsy RNA-seq (n=48; paired pre/post where available, n=31)
Public NSCLC resistance datasets (GSE165019, GSE103350, 6 additional cohorts)
DepMap CRISPR dependency data (EGFR-mutant cell lines)
Known resistance mechanisms: MET amp, EGFR C797S, SCLC transformation, EMT

Methods

Differential expression meta-analysis: resistant vs. sensitive (634 differentially regulated nodes)
Knowledge-graph GNN over KEGG cancer pathways + STRING protein interactions
Pathway bypass detection: identify activated pathways when EGFR node suppressed
Patient stratification clustering (k=5 resistance subtypes)

Output

634-node resistance network with centrality scores
5 resistance subtypes with prevalence estimates (MET amp 22%, FGFR bypass 14%, EMT 18%, cell-cycle escape 16%, unclassified 30%)
Pathway bypass map: 12 activated pathways in EGFR-suppressed context

Week 2: Target Prioritization for Combination Strategy

Combination target scoring integrated pathway centrality, druggability (approved/experimental inhibitors available), genetic dependency (DepMap), and patient subtype prevalence. Filtered 634 nodes to 47 combination-viable targets. Synergy prediction scoring (Bliss independence model on pathway orthogonality) ranked top pairs with osimertinib. Competitive landscape excluded 11 targets with existing Phase 3 combination trials. Safety overlay removed 6 targets with known class toxicity conflicts. Final pool: 23 targets across 5 resistance subtypes.

Week 3: Combination Dossiers and Protocol Support Package

Output

Top 8 combination targets with resistance dossiers (mechanism, prevalence, inhibitor precedent, biomarker)
23-target expanded list mapped to 5 resistance subtypes
Biomarker stratification panel: IHC/FISH/RNA signature per subtype
Phase 1b protocol appendix: inclusion biomarkers, combination rationale, futility boundaries
Synergy rationale matrix: target × osimertinib × resistance subtype
Validation experiment playbook (PDX models, organoids per subtype)

Combination Target List by Resistance Subtype

Top 8 combination targets with resistance dossiers mapped to 5 patient subtypes. Protocol appendix delivered for Phase 1b biomarker section.

Ranked resistance targets by subtype prevalence, druggability, and combination synergy score
Rank	Target	Resistance Subtype	Prevalence	Inhibitor Precedent	Status
1	MET	MET amplification	22%	Capmatinib, tepotinib (approved)	Priority A — known
2	FGFR1	FGFR bypass	14%	Erdafitinib (approved)	Priority A — novel combo
3	AXL	EMT / bypass	18%	Bemcentinib (Phase 2)	Priority A
4	CDK4/6	Cell-cycle escape	16%	Palbociclib (approved)	Priority A
5	SHP2 (PTPN11)	RTK bypass (multi)	12%	RMC-4630 (Phase 2)	Priority B
6	IGF1R	PI3K-AKT bypass	11%	Linsitinib (Phase 2)	Priority B
7	WEE1	Cell-cycle escape	9%	Adavosertib (Phase 2)	Priority B (novel)
8	TGFBR1	EMT / stromal	8%	Galunisertib (Phase 2)	Priority B

Results and impact

Speed, validation, and business outcomes

Speed vs. Internal Transcriptomics-Only Approach

Metric	Internal Bioinformatics	TargetIQ	Improvement
Timeline	8 to 10 weeks	3 weeks	3× faster
Cost	$350K (FTE + delayed protocol)	$210K	40% savings
Resistance Coverage	MET amp only (22%)	5 subtypes, 78% explained	Full resistance map
Protocol Support	None	Biomarker appendix + dossiers	Phase 1b ready
Novel Pathways	0 new mechanisms	3 novel bypass pathways	Differentiated combo strategy

Phase 1b Protocol Gate Outcomes (2 weeks post-delivery)

Clinical development committee review and PDX validation planning.

Target	Subtype	Committee Decision	Biomarker Selected?	Notes
MET	MET amp	Included — Arm A	Yes — FISH	Validates internal finding; combo arm confirmed
FGFR1	FGFR bypass	Included — Arm B	Yes — RNA signature	Novel arm; dossier synergy score cited
AXL	EMT	Included — Arm C	Yes — IHC	Biomarker panel from TargetIQ appendix adopted
CDK4/6	Cell-cycle	Backup arm	Yes — RB status	Deprioritized vs. FGFR; retained as expansion
SHP2	RTK bypass	Exploratory cohort	Partial	Pending PDX data; validation playbook delivered
Rank 6–8	Mixed	2/3 in expansion protocol	Yes	WEE1 flagged as novel; TGFBR1 stromal angle accepted

78%: Resistance cases mapped to subtype
3: Novel bypass pathways identified
3 wks: Protocol lock met (5-week deadline)
4: Combination arms in Phase 1b protocol

Immediate Wins

Phase 1b protocol locked on schedule with 4 combination arms and biomarker stratification panel
FGFR bypass pathway (14% prevalence) identified as novel combination opportunity—absent from internal analysis
Biomarker appendix adopted into protocol document with minimal clinical team edits
Resistance subtype framework enabled adaptive cohort expansion design

Strategic Advantages

Knowledge-graph bypass detection surfaced FGFR1 and SHP2 pathways not visible in single-gene differential expression
Patient stratification (k=5 clusters) converted unexplained 78% resistance into actionable subtypes
Synergy scoring matrix prioritized orthogonal combinations over redundant RTK stacking
DepMap dependency integration confirmed CDK4/6 and WEE1 in cell-cycle escape subtype with CRISPR evidence

Follow-on engagement
Q4 2025: FGFR1 combination lead optimization via HelixForge. Estimated cost: $320K. Target: ranked inhibitors within 3 weeks for preclinical combo PK/PD.

Model validation

Lessons and recommendations

What Worked

Proprietary biopsy integration (n=48) was essential—public cohorts alone missed FGFR bypass prevalence in client population
Pathway bypass GNN outperformed differential expression for ranking combination targets (AUC 0.81 vs. 0.67 for hit prediction)
Protocol appendix format reduced clinical team revision cycle from typical 3 weeks to 4 days
Resistance subtype labels adopted in internal program nomenclature

Challenges and Mitigations

30% of patients remained in unclassified subtype after initial clustering—insufficient biopsy depth for rare mechanisms.

Mitigation: Recommended liquid biopsy cfDNA panel for trial enrollment; added unclassified arm with exploratory RNA-seq budget in protocol.

SHP2 inhibitors in clinical development created competitive timing pressure for combination arm inclusion.

Mitigation: Competitive brief identified differentiated patient segment (RTK bypass, SHP2-high); positioned as exploratory rather than primary arm.

When to use TargetIQ for oncology resistance mapping

Acquired resistance after targeted therapy with unexplained patient population
Phase 1b/2 protocol lock requiring biomarker stratification and combination rationale
Proprietary post-progression biopsy or ctDNA data needing integration with public resistance cohorts
Combination strategy design requiring pathway orthogonality scoring beyond single-gene analysis

ROI: approximately 6:1 (protocol delay cost avoided ~$1.2M in program overhead + 40% bioinformatics cost savings + differentiated combo arms).

Next steps: execute Phase 1b with biomarker-enriched arms; feed response data back for resistance model refinement after 12 patients.

About This Engagement

Client profile: Top-20 pharma, oncology discovery unit, EGFR franchise team
Project duration: 3 weeks (computational delivery) + 2 weeks (protocol gate)
Total cost: $210K
Date: July to August 2025

This case study is anonymized at client request. Resistance prevalence estimates rounded; protocol details redacted. Full dossiers and pathway maps available under NDA.

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