Baseline lesion number as an efficacy predictive and independent prognostic factor and its joint utility with TMB for PD-1 inhibitor treatment in advanced gastric cancer

Xiao-Li Wei, Jian-Ying Xu, De-Shen Wang, Dong-Liang Chen, Chao Ren, Jia-Ning Li, Feng Wang, Feng-Hua Wang, Rui-Hua Xu, Xiao-Li Wei, Jian-Ying Xu, De-Shen Wang, Dong-Liang Chen, Chao Ren, Jia-Ning Li, Feng Wang, Feng-Hua Wang, Rui-Hua Xu

Abstract

Background: We previously reported tumor mutation burden (TMB) as a potential prognostic factor for patients with advanced gastric cancer (AGC) receiving immunotherapy. We aimed to comprehensively understand the impact of tumor burden and TMB on efficacy and prognosis in immunotherapy-treated AGC patients.

Methods: A total of 58 patients with refractory AGC receiving PD-1 inhibitor monotherapy from a phase Ib/II clinical trial (ClinicalTrials.gov identifier: NCT02915432) were retrospectively included. Univariate and multivariate logistical regression analyses and the Cox proportional hazards model were performed for prognostic value of baseline factors. Factors reflecting baseline tumor burden, including baseline lesion number (BLN), the maximum tumor size (MTS) and the sum of target lesion size (SLS) were analyzed. The objective response rate (ORR) and disease control rate (DCR) were compared by Chi-square test.

Results: In univariate analysis, high BLN was associated with poor median progression-free survival (mPFS) [1.7 months versus 3.4 months; hazard ratio (HR), 2.696, p < 0.05] and median overall survival (mOS) (3.2 months versus 7.6 months; HR, 1.997, p < 0.05), while high TMB was a positive prognostic factor. In multivariable analysis, both BLN and TMB were independent prognostic factors for mOS (BLN: HR, 2.782, p < 0.05; TMB: HR, 0.288, p < 0.05), while MTS or SLS had no association with survival. Better ORR and DCR were observed in the low BLN group (15.4% versus 5.3%, p > 0.05; 86.96% versus 54.29%, p < 0.05). When combining BLN and TMB, the best efficacy and survival were observed in the BLNlowTMBhigh group (ORR: 37.5%, DCR: 62.5%, mPFS and mOS: not reached). The worst efficacy and survival were shown in the BNLhighTMBlow group [ORR: 0% (0/15); DCR: 13.3%; mPFS: 1.7 months; mOS: 2.7 months (all p < 0.05)].

Conclusions: BLN, rather than factors regarding baseline tumor size, is perhaps a potential predictor for benefit from immunotherapy and its combination with TMB could further risk-stratify patients with AGC receiving immunotherapy.

Keywords: PD-1 inhibitor; baseline lesion number; gastric cancer; prognostic factor; tumor mutation burden.

Conflict of interest statement

Conflict of interest statement: The authors declare that there is no conflict of interest.

© The Author(s), 2021.

Figures

Figure 1.
Figure 1.
Kaplan–Meier plots of progression-free survival and overall survival stratified by BLN (BLN ⩽ 5/BLN > 5) in treatment-refractory advanced gastric cancer patients receiving PD-1 inhibitor. (a) Progression-free survival; (b) Overall survival. Patients with lower BLN (BLN ⩽ 5) had significantly superior median progression-free survival (3.4 months versus1.7 months, p < 0.001) and median overall survival (7.6 months versus 3.2 months,p < 0.05).BLN, baseline lesion number; PD-1, programmed cell death-1.
Figure 2.
Figure 2.
Kaplan–Meier plots of progression-free survival and overall survival stratified by BLN (BLN ⩽ 5/BLN > 5) and TMB (TMB ⩽ 12Muts/Mb/TMB > 12Muts/Mb) in treatment-refractory advanced gastric cancer patients receiving PD-1 inhibitor. (a) Progression-free survival; (b) Overall survival. Patients were stratified into three subgroups: BLNlowTMBhigh (n = 8), BLNhighTMBhigh or BLNlowTMBlow (n = 31) and BLNhighTMBlow (n = 15). The progression-free survival and overall survival was the best for BLNlowTMBhigh group and the worst for BLNhighTMBlow group (bothp < 0.05).BLN, baseline lesion number; PD-1, programmed cell death-1; TMB, tumor mutation burden.

References

    1. Ferlay J, Soerjomataram I, Dikshit R, et al. Cancer incidence and mortality worldwide: sources, methods and major patterns in GLOBOCAN 2012. Int J Cancer 2015; 136: E359–E386.
    1. Catalano V, Labianca R, Beretta GD, et al. Gastric cancer. Crit Rev Oncol Hematol 2009; 71: 127–164.
    1. Gao K, Wu J. National trend of gastric cancer mortality in China (2003-2015): a population-based study. Cancer Commun (Lond) 2019; 39: 24.
    1. Muro K, Van Cutsem E, Narita Y, et al. Pan-Asian adapted ESMO clinical practice guidelines for the management of patients with metastatic gastric cancer: a JSMO-ESMO initiative endorsed by CSCO, KSMO, MOS, SSO and TOS. Ann Oncol 2019; 30: 19–33.
    1. Wang FH, Shen L, Li J, et al. The Chinese Society of Clinical Oncology (CSCO): clinical guidelines for the diagnosis and treatment of gastric cancer. Cancer Commun (Lond) 2019; 39: 10.
    1. Fuchs CS, Doi T, Jang RW, et al. Safety and efficacy of pembrolizumab monotherapy in patients with previously treated advanced gastric and gastroesophageal junction cancer: phase 2 clinical KEYNOTE-059 trial. JAMA Oncol 2018; 4: e180013.
    1. Kang YK, Boku N, Satoh T, et al. Nivolumab in patients with advanced gastric or gastro-oesophageal junction cancer refractory to, or intolerant of, at least two previous chemotherapy regimens (ONO-4538-12, ATTRACTION-2): a randomised, double-blind, placebo-controlled, phase 3 trial. Lancet 2017; 390: 2461–2471.
    1. De Rosa S, Sahnane N, Tibiletti MG, et al. EBV⁺ and MSI gastric cancers harbor high PD-L1/PD-1 expression and high cD8⁺ intratumoral lymphocytes. Cancers (Basel) 2018; 10: 102.
    1. Dudley JC, Lin MT, Le DT, et al. Microsatellite instability as a biomarker for PD-1 blockade. Clin Cancer Res 2016; 22: 813–820.
    1. Karpińska-Kaczmarczyk K, Lewandowska M, Ławniczak M, et al. Expression of mismatch repair proteins in early and advanced gastric cancer in Poland. Med Sci Monit 2016; 22: 2886–2892.
    1. Topalian SL, Taube JM, Anders RA, et al. Mechanism-driven biomarkers to guide immune checkpoint blockade in cancer therapy. Nat Rev Cancer 2016; 16: 275–287.
    1. Büttner R, Gosney JR, Skov BG, et al. Programmed death ligand 1 immunohistochemistry testing: a review of analytical assays and clinical implementation in non-small-cell lung cancer. J Clin Oncol 2017; 35: 3867–3876.
    1. Mishima S, Kawazoe A, Nakamura Y, et al. Clinicopathological and molecular features of responders to nivolumab for patients with advanced gastric cancer. J Immunother Cancer 2019; 7: 24.
    1. Herbst RS, Soria JC, Kowanetz M, et al. Predictive correlates of response to the anti-PD-L1 antibody MPDL3280A in cancer patients. Nature 2014; 515: 563–567.
    1. Kim ST, Cristescu R, Bass AJ, et al. Comprehensive molecular characterization of clinical responses to PD-1 inhibition in metastatic gastric cancer. Nat Med 2018; 24: 1449–1458.
    1. Cristescu R, Mogg R, Ayers M, et al. Pan-tumor genomic biomarkers for PD-1 checkpoint blockade-based immunotherapy. Science 2018; 362: eaar3593.
    1. Muro K, Chung HC, Shankaran V, et al. Pembrolizumab for patients with PD-L1-positive advanced gastric cancer (KEYNOTE-012): a multicentre, open-label, phase 1b trial. Lancet Oncol 2016; 17: 717–726.
    1. Sidaway P. Immunotherapy-responsive gastric cancers identified. Nat Rev Clin Oncol 2018; 15: 590.
    1. Wang F, Wei XL, Wang FH, et al. Safety, efficacy and tumor mutational burden as a biomarker of overall survival benefit in chemo-refractory gastric cancer treated with toripalimab, a PD-1 antibody in phase Ib/II clinical trial NCT02915432. Ann Oncol 2019; 30: 1479–1486.
    1. Joseph RW, Elassaiss-Schaap J, Kefford R, et al. Baseline tumor size is an independent prognostic factor for overall survival in patients with melanoma treated with pembrolizumab. Clin Cancer Res 2018; 24: 4960–4967.
    1. Suzuki C, Kiyota N, Imamura Y, et al. Effect of tumor burden and growth rate on treatment outcomes of nivolumab in head and neck cancer. Int J Clin Oncol 2020; 25: 1270–1277.
    1. Nesseler JP, Lee MH, Nguyen C, et al. Tumor size matters-understanding concomitant tumor immunity in the context of hypofractionated radiotherapy with immunotherapy. Cancers (Basel) 2020; 12: 714.
    1. Hopkins AM, Kichenadasse G, McKinnon RA, et al. Baseline tumor size and survival outcomes in lung cancer patients treated with immune checkpoint inhibitors. Semin Oncol 2019; 46: 380–384.
    1. Friedlander P. The use of baseline tumor size to prognosticate overall survival in stage IV melanoma patients treated with the PD-1 inhibitor pembrolizumab. Ann Transl Med 2019; 7: S24.
    1. Miyawaki T, Kenmotsu H, Mori K, et al. Association between clinical tumor burden and efficacy of immune checkpoint inhibitor monotherapy for advanced non-small-cell lung cancer. Clin Lung Cancer 2020; 21: e405–e414.
    1. Eisenhauer EA, Therasse P, Bogaerts J, et al. New response evaluation criteria in solid tumours: revised RECIST guideline (version 1.1). Eur J Cancer 2009; 45: 228–247.
    1. Ferrara R, Mezquita L, Texier M, et al. Hyperprogressive disease in patients with advanced non-small cell lung cancer treated with PD-1/PD-L1 inhibitors or with single-agent chemotherapy. JAMA Oncol 2018; 4: 1543–1552.
    1. Kanda M, Mizuno A, Fujii T, et al. Tumor infiltrative pattern predicts sites of recurrence after curative gastrectomy for stages 2 and 3 gastric cancer. Ann Surg Oncol 2016; 23: 1934–1940.
    1. Saito H, Miyatani K, Takaya S, et al. Tumor infiltration pattern into the surrounding tissue has prognostic significance in advanced gastric cancer. Virchows Arch 2015; 467: 519–523.
    1. Zhao Y, Xu E, Yang X, et al. Tumor infiltrative growth pattern correlates with the immune microenvironment and is an independent factor for lymph node metastasis and prognosis in stage T1 esophageal squamous cell carcinoma. Virchows Arch 2020; 477: 401–408.
    1. Ito E, Ozawa S, Kijima H, et al. New invasive patterns as a prognostic factor for superficial esophageal cancer. J Gastroenterol 2012; 47: 1279–1289.
    1. Ebisumoto K, Okami K, Ogura G, et al. The predictive role of infiltrative growth pattern in early pharyngeal cancers. Acta Otolaryngol 2015; 135: 1172–1177.
    1. Garner H, de Visser KE. Immune crosstalk in cancer progression and metastatic spread: a complex conversation. Nat Rev Immunol 2020; 20: 483–497.
    1. Maman S, Witz IP. A history of exploring cancer in context. Nat Rev Cancer 2018; 18: 359–376.
    1. Fujiyoshi K, Yamaguchi T, Kakuta M, et al. Predictive model for high-frequency microsatellite instability in colorectal cancer patients over 50 years of age. Cancer Med 2017; 6: 1255–1263.
    1. Lee SY, Kim DW, Lee HS, et al. Low-level microsatellite instability as a potential prognostic factor in sporadic colorectal cancer. Medicine 2015; 94: e2260.
    1. Kim JY, Shin NR, Kim A, et al. Microsatellite instability status in gastric cancer: a reappraisal of its clinical significance and relationship with mucin phenotypes. Korean J Pathol 2013; 47: 28–35.
    1. Zhang D, He W, Wu C, et al. Scoring system for tumor-infiltrating lymphocytes and its prognostic value for gastric cancer. Front Immunol 2019; 10: 71.
    1. Huang AC, Postow MA, Orlowski RJ, et al. T-cell invigoration to tumour burden ratio associated with anti-PD-1 response. Nature 2017; 545: 60–65.

Source: PubMed

Sponsors and Collaborators

Medical Conditions

Drug Interventions

3
Subscribe