Prognose mittels Genexpression

Prof. Martin H. Brutsche

Kantonsspital St. Gallen-CH

Introduction

Targeted therapies show low activity when given to all NSCLC, but are very effective in subsets of patients → Personalization

Diagnostic refinements → identification of subgroupsPrognostic markersPredictive markers

Progress is dependent on todays patients → Role for biobanking & high-throughput technologies

Precise histo-pathologic PhenotypingGenetics & Genomics & Proteomics

Targeted therapy – Need for personalization

Introduction

Pros of Gene Expression AnalysisFocused view on utilized gene codeIs the basis of all downstream products, i.e. peptides & proteinsHigh technical standards allow genome-wide analysisGives quantitative results (Genetics → Y/N)Allows dynamic analyses → Early response measures

Role for Gene Expression Analyses?

2007

Only high-risk patients (A&C) profit from adjuvant CT

JCO 2010

Data processingThe power of multivariate statistics

• Acceptable rules for data preprocessing, normalization, classical statistical testing, correction for multiple testing…

• Multivariate statistics allows a better analysis of gene expression similarities, i.e. potential “relationships”

• Here an example from our kitchen…

BMC Bioinformatics 2008

Issues of PracticabilityGene expression from easy accessible source

• Due to advanced stages most patients are not suitable for curative surgery

no surgical bx available• Is tumour cell enrichment necessary?

– For Genetics Y– For Genomics maybe not– For Proteomics ?

• Need for specimen from minimally invasive procedures– Bronchoscopic samples, i.e. cytobrush or biopsy– CT-guided biopsy– Blood samples

AJRCCM 2010

Heterogeneity of tumor cell contentInfluence on diagnosis but not on prognosis

AJRCCM 2010

Little Overlap of Signature GenesLimitations of Gene Expression Signatures

• Reasons for technical variability– Differences between platforms– Different handling & storage SOPs– Single vs. multi center shipment…– Fresh-frozen vs. formalin-embedded tissue– Probes with tumour cell enrichment, e.g. LCM?

• Biological redundancy– Genome-wide analyses capture redundancy of co-

regulated gene families

• Insufficiently controlled co-factors like smoking status

Inclusion

Bevacizumab 15mg/kg i.v.q3w + Erlotinib 150mg/d p.o.

Gemcitabine 1250mg/m2

+ Cisplatin 80mg/m2 or Carboplatin AUC 5

q3w x 6 or until progression

Follow-upuntil progression or toxicity

Targeted Therapy Chemotherapy

Primary Endpoint: DSR @ 12 weeks 55 (44-64) % Secondary Endpoint: TTP 4 (2.9-5.5) months Responses: PD 41, SD 44, PR 10, CR 1 OS 13 (10.5-19.4) months

Exonic expression variations of EGFR and KRAS in small bronchoscopic biopsies from patients with advanced non-small cell lung cancer treated by combined bevacizumab-

erlotinib therapy followed by platinum-based chemotherapy at disease progression

A multicenter phase II trial SAKK 19/05M.H. Brutsche, M. Frueh, S. Crowe, K.J. Na, C. Droege, D.C. Betticher, R. Cathomas, R. von Moos, F. Zappa, M. Pless, L. Bubendorf, F. Baty

• 101 treatment-naive non-squamous stage IIIB/IV

Conclusion

Lung Cancer is an orphan diseaseFeasibility & validity proven for

Batched analyses within clinical trialsAdvanced statistical methods availablePrediction of early relapse after curative resectionSmall bronchoscopic biopsies in all disease stages

Open issuesAnalyses of individual day-to-day samplesUtility of genomics from peripheral bloodTumour cell enrichment – if and when?Which signature gene set to be used?

FutureSubgenic analysis

Prognostic Gene Expression Signatures