In:
Cancer Research, American Association for Cancer Research (AACR), Vol. 81, No. 13_Supplement ( 2021-07-01), p. 662-662
Kurzfassung:
Motivation. A blood-based proteomic host immune classifier (HIC) that identifies a patient's disease state as Hot or Cold can aid prognostication and help guide treatment decisions in non-small cell lung cancer (NSCLC). The HIC Hot label is associated with 2-2.5 times longer overall survival (OS) depending on treatment type. While pretreatment HIC labels are informative, label flips over the course of therapy have been observed. We sought to quantify the prevalence of label flips, determine their impact on prognosis, and investigate the utility of longitudinal testing to monitor changes in disease state throughout therapy. Methods. In a real-world observational study (NCT03289780) enrolling over 3,700 patients with NSCLC at any stage and line of therapy to date, 267 of 1464 patients with advanced (Stage 3b/4) NSCLC with at least 1 year follow-up (f/u) had longitudinal testing at first f/u. Patient disease states were designated HH (Hot baseline and f/u), HC (Hot baseline, Cold f/u), CH (Cold baseline, Hot f/u) or CC (Cold baseline and f/u). Results. For patients receiving all therapy lines and regimens, 38 of 209 patients with baseline Hot test result (18%) flipped to Cold (HC), whereas 28 of 58 patients with baseline Cold, (48%) flipped (CH) (table). Patients with a baseline Hot result (HH+HC) had significantly longer OS compared to baseline Cold (CH+CC). Comparing patient groups based on f/u result (HH+CH vs. HC+CC) yielded an even greater separation. Similar trends were observed in the subgroup of patients receiving chemotherapy (n=124), with 18 patients flipping from Hot to Cold (20%), and 12 from Cold to Hot (36%) at f/u. Average time to f/u (TTF) was 6 months and did not vary significantly between groups. Conclusions. For some patients with NSCLC, disease states and prognosis can change in response to therapy. Longitudinal proteomic testing may be a viable method to monitor changes in disease state and host immune response to guide treatment. Survival of study subjectsGroupmOS [95% CI], monthsMean TTF (SD) [95% CI] , monthsTotal (N=267)6.12 (3.70) [5.67-6.56]HH (N=171)NR [17.0-und] 5.65 (3.50) [4.01-7.29]HC (N=38)11.6 [9.2-und] 5.94 (3.31) [4.86-7.03]CH (N=20)NR [11.6-und] 6.30 (3.91) [5.71-6.89]CC (N=38)10.2 [7.9-17.4] 5.71 (3.19) [4.67-6.76]Total (N=267)HR [95% CI] P valueHH vs. HC1.81 [1.11-2.96]0.018HH vs. CH1.03 [0.47-2.24] 0.946HH vs. CC2.56 [1.60-4.10] & lt;0.0001HC vs. CH0.59 [0.25-1.40]0.234HC vs. CC1.40 [0.78-2.52] 0.260CH vs. CC2.38 [1.02-5.54]0.045All Tx (N=267)mOS [95% CI] , monthsHR [95% CI], P valueHH+HC (N=209)NR [16.6-und] 0.59 [0.39-0.89], P=0.012CH+CC (N=58)12.9 [9.3-und] HH+CH (N=191)NR [17.5-und]0.47 [0.33-0.69] , P & lt;0.0001HC+CC (N=76)11.6 [9.3-16.4]Chemo (N=124)mOS [95% CI] , monthsHR [95% CI], P valueHH+HC (N=91)NR [15.3-und] 0.52 [0.31-0.88], P=0.015CH+CC (N=33)11.6 [7.9-17.9] HH+CH (N=85)NR [15.6-und]0.42 [0.25-0.70] , P & lt;0.001HC+CC (N=39)9.6 [7.9-16.4]All Tx, all treatment; Chemo, chemotherapy ; CI, confidence interval; HR, hazard ratio; NR, not reached; SD, standard deviation; TTF, time to follow-up; und, undefined Citation Format: Eric Schaefer, R. Brian Mitchell, Jason Boyd, James Orsini, Nagaprasad Nagajothi, Savita Bidyasar, Mazen Khalil, Mitchell Haut, Ray Page, Kan Huang, John W. Dubay, Wallace Akerley. Longitudinal blood-based proteomic testing in advanced non-small cell lung cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2021; 2021 Apr 10-15 and May 17-21. Philadelphia (PA): AACR; Cancer Res 2021;81(13_Suppl):Abstract nr 662.
Materialart:
Online-Ressource
ISSN:
0008-5472
,
1538-7445
DOI:
10.1158/1538-7445.AM2021-662
Sprache:
Englisch
Verlag:
American Association for Cancer Research (AACR)
Publikationsdatum:
2021
ZDB Id:
2036785-5
ZDB Id:
1432-1
ZDB Id:
410466-3
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