Sarcopenia: A Possible Biomarker Relevant to ICI Response: History
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Subjects: Oncology

Sarcopenia and changes in muscle mass during a certain treatment period have been evaluated as important prognosticators in cancer patients, while immunotherapy with immune checkpoint inhibitors (ICIs) has become one of the major breakthroughs in advanced cancers. Therefore, sarcopenia appears to be an effective biomarker for predicting long-term oncologic outcomes in patients receiving ICI therapy and hence plays an important role when making treatment decisions.

  • sarcopenia
  • immune checkpoint inhibitors
  • overall survival
  • progression-free survival

1. Introduction

The clinical benefits and side effects of immune checkpoint inhibitors (ICIs) vary, and they include hyperprogression among patients with cancer [1][2][3]. Therefore, investigating the biomarkers relevant to ICI response is important for predicting patients’ clinical outcomes. Recently, the clinical significance of sarcopenia in patients who have undergone ICI therapy has been reported. Cortellini et al. reported that a low skeletal muscle index (SMI) was associated with poor oncologic outcomes in advanced cancer patients treated with ICIs [4]. Shimizu et al. reported that the psoas muscle index (PMI) might be a significant prognostic factor for progression-free survival (PFS) and overall survival (OS) following ICI therapy for metastatic urothelial carcinoma [5]. In contrast, Minami et al. observed no significant correlation between sarcopenia and clinical outcomes in patients treated with ICIs [6]. Although a recent meta-analysis reported that sarcopenia could be used as a viable option for predicting prognosis in non-small cell lung cancer (NSCLC) patients who received ICIs [7], the impact of sarcopenia has not been thoroughly investigated in patients with other types of cancer.

2. Study Population Characteristics

The details of the included studies are presented in Table 1. All the included studies had a retrospective design. The majority of the cancer types in the included studies were NSCLC (7), followed by hepatocellular carcinoma (2), melanoma (2), urothelial carcinoma (2), renal cell carcinoma, and gastric cancer. In terms of the types of ICIs, 13 studies used anti-PD-1/PD-L1 ICIs, and only one study used anti-CTLA-4. The cut-off values and sarcopenia reference varied across studies. SMI was used to define sarcopenia in 10 studies, whereas PMI was used to measure sarcopenia in 4 studies.

Table 1. Characteristics of the studies included in the meta-analysis.
Author, Year Country Cancer Stage Time Point of CT Exam a ICI Type Measurement of Sarcopenia Cut-Off Value of Sarcopenia b No. of Patients Median Age of Patients No. of Sarcopenia(%)
Minami 2020 [6] Japan NSCLC Advanced 90 days Nivolumab, Pembrolizumab, Atezolizumab PMI Male:6.36, Female:3.92 74 70 53(71)
Magri 2019 [8] Italy NSCLC Stage IV 10 weeks Nivolumab SMI NA 46 65 NA
Roch 2020 [9] France NSCLC Metastatic NA Nivolumab, Pembrolizumab SMI Male: 52.4, Female: 38.5 142 64 92(66)
Shiroyama 2019 [10] Japan NSCLC Advanced 90 days Nivolumab, Pembrolizumab PMI Male:6.36, Female:3.92 42 71 22(52)
Takada 2020 [11] Japan NSCLC Stage III, IV/Recurred NA Nivolumab, Pembrolizumab SMI Male: 25.63, Female: 21.73 103 67 51(49)
Tsukagoshi 2020 [12] Japan NSCLC Stage III, IV 30 days Nivolumab PMI Male:6.36, Female:3.92 30 67 13(43)
Akce 2020 [13] USA HCC Advanced 2 months Anti PD-1, Anti-PD-1 + others(not specified) SMI Male: 43, Female: 39 57 66 28(49)
Kim N 2020 [14] Korea HCC Advanced NA Nivolumab SMI Male: 42, Female: 38 102 61 23(23)
Chu 2020 [15] Canada Melanoma Metastatic/ advanced 30 days Ipilimumab SMI Male: 43(52 c), Female: 41 97 56 NA
Young 2020 [16] USA Melanoma Metastatic/ advanced 6 months Nivolumab, Pembrolizumab, Atezolizumab, Ipilimunab + nivolumab SMI Male: 43(52 c), Female: 41 287 63 154(54)
Shimizu 2020 [5] Japan Urothelial carcinoma Metastatic/ advanced NA Pembrolizumab PMI Male:6.36, Female:3.92 27 73 15(56)
Fukushima 2020 [17] Japan Urothelial carcinoma Advanced 30 days Pembrolizumab SMI Male: 43(52 c), Female: 41 28 74 19(68)
Kim Y 2020 [18] Korea Gastric cancer Metastatic 3 months Nivolumab, Pembrolizumab SMI Male: 49, Female: 31 149 57 79(53)
Cortellini 2020 [4] Italy NSCLC, Melanoma, RCC, others Advanced 90 days Pembrolizumab, Nivolumab, Atezolizumab, and others SMI Male: 48.4(50.2 c), Female: 36.9(59.6 c) 100 66 50(50)
Abbreviations: ICI, immune-checkpoint inhibitor; NSCLC, non-small cell lung cancer; HCC, hepatocellular carcinoma; NA, not available; SMI, skeletal muscle index; PMI, psoas muscle index; a: time within initiation of ICI therapy; b: cm2 /m2c: patient with body mass index >25kg/m2.

3. The Biomarkers Relevant to ICI Outcomes

Since ICIs were introduced as an alternative treatment option in various advanced and refractory cancer patients [19], identifying the biomarkers relevant to ICI outcomes has been actively investigated. Higher tumor mutational burden, microsatellite instability, and PD-L1 immunohistochemical staining have been proven to be strong predictive markers for better responses [20]. However, these biomarkers are difficult to use because additional laborious work or obtaining adequate tissue is required. Recently, a growing body of evidence has reported that patient host factors, such as body composition, are associated with the clinical efficacy of ICIs. Sarcopenia, which was initially defined as age-associated loss of muscle mass in elderly persons [21], has been incorporated into the oncology field, and the prognostic impact of sarcopenia or myosteatosis in cancer patients treated with surgery and/or palliative or adjuvant chemotherapy has been well studied [22][23][24]. Most patients diagnosed with a certain type of cancer underwent abdominopelvic CT to determine the extent of the disease at the initial stage. The lack of additional demand to assess sarcopenia is a very important advantage in terms of clinical use.

The impact of sarcopenia on ICIs can be explained in several ways. Chronic inflammation in cancer, a major contributor to the sarcopenia cascade [25], causes immune dysfunction, such as T cell exhaustion, which is characterized by a loss of effector function, prolonged and high expression of multiple inhibitory receptors, and specific transcriptional pathways [26]. It is mediated by changes in the functions of cytokines and results in a reduced response of ICIs. In addition, skeletal muscle tissue synthesizes cytokines and other proteins. They are collectively called myokines. Myokines, such as IL-6, IL-15, TNF-α, and TGF-β, exert autocrine, endocrine, and paracrine effects on many tissues. With altered activities of these myokines in the setting of sarcopenia, the immune system leans towards exhibiting pro-inflammatory effects and muscle catabolism, as well as inducing immune senescence [27][28]. Additionally, the role of gut microbiome in developing sarcopenia and modulating ICIs’ responses was recently introduced. The gut microbiome is extensively involved in the immune system by anatomic features and the need to modulate the numerous variant species in the gastrointestinal tract. In patients with altered gut microbiome, the gut dysbiosis may result in promoting a pro-inflammatory pathway related to sarcopenia. However, the pathophysiology of the role of gut microbiome to regulate the response to ICIs was not fully investigated yet [29][30].

Whether sarcopenia could be used as a predictive marker for immune-related adverse events (irAEs) remains unclear. A recent meta-analysis by Wang et al. reported that sarcopenia was not associated with an increased rate of irAEs (relative risk = 0.99, 95% CI = 0.21–4.67) in patients with NSCLC [7]. Another systematic review reported that sarcopenia was correlated with adverse events; however, no association with increased irAEs was noted [31]. Therefore, it is unclear whether poor oncologic outcomes for sarcopenic patients are directly derived from ICI-induced toxicities or reduced adherence to ICI treatments. Further research needs to be done to reveal the fundamental mechanism of this correlation.

This entry is adapted from the peer-reviewed paper 10.3390/jcm10225329


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