Age at Diagnosis (yrs)

Median 65.58

Mean 64.32

Gender

Female 43 60%

Male 29 40%

Race

Caucasian 59 82%

African American 11 15%

Asian/pacific Islander 3 3%

Other 1 1%

Definitive

No (Surgical) 13 18%

Yes 59 82%

Smoking Status

No 10 14%

Yes 62 86%

Stage at consent

Stage IV 72 100%

Histopathology

Adenocarcinoma 46 64%

Squamous Cell 10 14%

Large Cell 2 3%

Other 14 19%

Performance Status

0 8 11%

1 23 32%

1.5 2 3%

2 4 6%

<NA> 35 49%

Development of a serum biomarker panel predicting clinical outcome of chemotherapy with pemetrexed in patients with NSCLCRUSH UNIVERSITY

MEDICAL CENTERMarta Batus, MD; Jeffrey A. Borgia, PhD*; Mary J Fidler, MD; Shruthi Melinamani, MD; Ravi Pithadia, MD; Sanjib Basu, PhD; Cristina Fhied, MS; Brett Mahon, MD; and

Philip Bonomi, MD

Pemetrexed disodium is a novel folate antimetabolite approved

for first-line treatment in combination with a platinum doublet,

for second-line treatment as a single agent and, more recently,

as maintenance treatment after first-line chemotherapy in

patients with non-squamous non-small cell lung cancer

(NSCLC).

Circulating factors associated with folate metabolism and/or

phenotypic plasticity (e.g. the epithelial-to-mesenchymal

transition (EMT)) may have predictive value in selecting

advanced NSCLC for first-line pemetrexed.

BACKGROUND Pretreatment serum from a total of 72 patients with non-squamous stage IV NSCLC was evaluated with 76 biomarkers using Luminex immunobead assays.

Patients were treated either with platinum combined with pemetrexed (“P”: n= 26) or with other agents (“O”; n=51) at the discretion of the treating physician.

Patients were evaluated for disease progression using RECIST criteria.

Biomarker data was processed using Ingenuity Pathway Analysis (IPA) Suite to identify interactions with folate metabolism.

Cox Proportional Hazard (PH) regression model was used to assess association between H-scores and progression-free/overall survival (PFS/OS) distribution estimates.

PH interaction model was used to capture the differential effects of the biomarkers on the O vs. P treatment groups.

METHODS

Univariate PH regression analysis identified 10 biomarkers that were negatively associated (p<0.05) with progression-free survival (PFS) in either the O (sTNF-RI, sTNF-RII, Tenascin C, sIL-2Rα,

spg130, sIL-6R, CA-125, and CA 19-9) or the P subgroups (total PSA, amphiregulin).

Four other biomarkers (MMP-1, MMP-2, sVEGFR2, and PDGF-B) were all significantly (p<0.05) positively associated with PFS in the P group.

Similarly, seven biomarkers were strongly negatively associated (p<0.01) with overall survival (OS) in the O group, including osteopontin, sTNF-RI, sTNF-RII, CA 15-3, sIL-2Rα, CYFRA 21.1, and IL-

6; whereas the P group possessed both negative (osteopontin and amphiregulin) and positive (sVEGFR2, MMP-1, MMP-2, and sRAGE) associations (P<0.05) with OS.

Results of the p-value of interaction are below:

RESULTS

Serum biomarkers with potential predictive (PFS, OS) value for selecting patients most likely to benefit from pemetrexed have been identified.

Pathway analysis demonstrates interactions of biomarker candidates identified with folate metabolism.

This study is currently being expanded with additional front-line patients (P=90; n=56) from our institutional archives to further evaluate their potential predictive value.

CONCLUSIONS

DEMOGRAPHICS

The objective of this study was to identify serum biomarkers

capable of predicting improved outcomes for pemetrexed

added to first-line platinum based chemotherapy relative to

standard platinum doublet.

OBJECTIVE

0 10 20 30 40

0.0

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Cox PH model based prediction

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Alimta=0, MMP.1 = 2000Alimta=0, MMP.1 = 10000Alimta=1, MMP.1 = 2000Alimta=1, MMP.1 =10000

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Cox PH model based prediction

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Alimta=0, Anti.HGF = 100Alimta=0, Anti.HGF = 500Alimta=1, Anti.HGF = 100Alimta=1, Anti.HGF = 500

0 10 20 30 40

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Cox PH model based prediction

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Alimta=0, Anti.Total.PSA = 10Alimta=0, Anti.Total.PSA = 1000Alimta=1, Anti.Total.PSA = 10Alimta=1, Anti.Total.PSA = 1000

0 10 20 30 40 50 60

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Cox PH model based prediction

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rall

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Alimta=0, Anti.OPN = 20000Alimta=0, Anti.OPN = 50000Alimta=1, Anti.OPN = 20000Alimta=1, Anti.OPN = 50000

0 10 20 30 40 50 60

0.0

0.2

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Cox PH model based prediction

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rall

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Alimta=0, sIL.6R = 8000Alimta=0, sIL.6R = 20000Alimta=1, sIL.6R = 8000Alimta=1, sIL.6R = 20000

0 10 20 30 40 50 60

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Cox PH model based prediction

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Alimta=0, sVEGFR2 = 10000Alimta=0, sVEGFR2 = 20000Alimta=1, sVEGFR2 = 10000Alimta=1, sVEGFR2 = 20000

Biomarker Only analysis in the Continuous Scale

Therapy-Biomarker Interaction Analysis

Pemetrexed-ONLY subset(“P”)

Chemo Only subset(“O”)

ProgressionFree Survival HR p-value

n interaction model HR p-value n HR p-value n

MMP-1 0.39 0.0098 72 1.28 0.0640 47 0.39 0.0199 25HGF 0.63 0.0266 72 1.33 0.0769 47 0.86 0.2665 25Total PSA 40.68 0.0300 72 1.19 0.1343 47 1371 0.0016 25Tenascin C 0.15 0.0399 42 2.03 0.0075 29 0.38 0.2766 13Amphiregulin 4.51 0.0408 42 1.05 0.7634 29 11.39 0.0361 13sVEGFR2 0.40 0.0452 72 1.18 0.1717 47 0.36 0.0281 25

Overall SurvivalOsteopontin (OPN) 0.41 0.0042 76 3.86 0.0000 50 1.96 0.0136 26HGF 0.47 0.0052 76 1.62 0.0040 50 0.81 0.3058 26sIL-6R 0.49 0.0097 76 1.71 0.0067 50 0.91 0.6108 26MMP-2 0.38 0.0171 76 1.20 0.2252 50 0.42 0.0307 26sVEGFR2 0.34 0.0208 76 1.13 0.2762 50 0.28 0.0078 26sTNFRI 0.53 0.0213 76 1.92 0.0000 50 1.08 0.7385 26Tenascin C 0.11 0.0260 42 3.43 0.0037 29 0.31 0.1924 13MMP-1 0.36 0.0290 76 1.16 0.3291 50 0.36 0.0304 26

* - Corresponding Author: Email : Jeffrey_Borgia@rush.edu

p=0.0098 p=0.030 p=0.0266

p=0.0042 p=0.0097 p=0.0208