Skip to main content

Metabolic activity via 18F-FDG PET/CT is predictive of microsatellite instability status in colorectal cancer

Abstract

Purpose

Identification of microsatellite instability high (MSI-H) colorectal cancer (CRC) is crucial for screening patients most likely to benefit from immunotherapy. We aim to investigate whether the metabolic characteristics is related to MSI status and can be used to predict the MSI-H CRC.

Methods

A retrospective analysis was conducted on 420 CRC patients who were identified via [18F]fluorodeoxyglucose (18F-FDG) positron emission tomography (PET)/computed tomography(CT) prior to therapy. Maximum standardized uptake (SUVmax), mean standardized uptake (SUVmean), metabolic tumor volume (MTV) and total lesion glycolysis (TLG) of the primary tumor were calculated and compared between MSI-H and microsatellite stability (MSS). Predictive factors of MSI status were selected from metabolic parameters and clinicopathological profiles via a multivariate analysis.

Results

Of 420 colorectal cancers, 44 exhibited a high incidence of MSI. Both MTV and TLG were significantly higher in MSI-H group compared with the MSS group (P = 0.004 and P = 0.010, respectively). Logistic regression analysis indicated that CRC with MSI-H were related to younger age (P = 0.013), primary lesion located at right hemi-colon (P < 0.001) and larger MTV on PET/CT imaging (P = 0.019). MTV more than 32.19 of colorectal cancer was linked to the presence of MSI (P = 0.019).

Conclusion

Tumor metabolic burden were higher in MSI-H CRC which may be useful for predicting the MSI status of CRC patient and thus aid in determination of immunotherapy for patients with CRC.

Peer Review reports

Introduction

Colorectal cancer (CRC) is one of the most common malignancies and major cause of cancer-related death worldwide [1, 2]. Despite rapidly evolving in diagnosis and treatment these years, the prognosis of metastatic CRC (mCRC) patients remains poor, with a median overall survival (OS) of approximately 30 months [3]. The progression of more novel and effective therapeutic strategies is an urgent unmet need for CRC patients. Several advances from the past few years indicate the potential to prolong patient survival through effectiveness of treatments based on an individual’s tumor-specific biomarkers [4,5,6]. Arguably, the most prominent examples are provided by the successes with anti-programmed cell death 1 (PD-1) in CRC contributed by the selection of microsatellite instability high (MSI-H) [7], which were granted approval by the U.S. Food and Drug Administration (FDA) for MSI-H mCRC patients in May 2017 [8]. Several prospective clinical trials in chemotherapy-resistant MSI mCRC have demonstrated a high disease control rate (DCR) and a favorable progression-free survival (PFS) with immune checkpoint inhibitors (ICPIs) [6, 9]. However, reported response rates (RR) of 23–69% and DCR of 47–89% to ICPIs in MSI-H CRC are likely reflecting patient and/or tumor heterogeneity [6, 10, 11]. Selecting CRC patients with MSI-H will be exceptionally useful in screening out patients most likely to benefit from immunotherapy to prolong patient survival and improve prognosis.

Currently, there are three major methods for detecting MSI status, including immunohistochemistry (IHC), polymerase chain reaction (PCR) and next-generation sequence (NGS) [12]. Although these analyses of CRC samples have been incorporated into routine clinical practice for the purpose of treatment algorithms, the heterogeneity of MSI-H status, poor DNA quality of biopsy samples, the invasive procedure, or/and the long experiment period may become limiting factors in their clinical application [13, 14]. Therefore, alternative noninvasive strategies could therefore be of good choice.

Fluorine 18 (18F) fluorodeoxyglucose (FDG) PET/CT is a valuable molecular imaging modality that is a less invasive tool in the management of patients with CRC [15] . Despite imaging techniques being critical in the preoperative workup for diagnosis or prognostication, some correlation exist between pretreatment image findings and genomic expression in malignant disease, such as c-Met status in gastric cancer [16] and PD-L1 expression in lung cancer [17]. Similarly, Chung et al. have shown MSI status to be correlated with 18F-FDG uptake in gastric cancer [18]. Thus, we hypothesized that the pretreatment 18F-FDG PET/CT might be a helpful tool for non-invasively inferring the MSI-H CRC patients.

Therefore, our purpose was to explore the relationship between metabolic parameters, clinicopathological profiles and MSI expression in CRC patients.

Materials and methods

Study design and patients

The Investigational Review Board of Peking University Cancer Hospital approved the present study (IRB number: 2022YJZ48). The requirement to acquire informed consent was waived owing to the Ethics Committee of Peking University Cancer Hospital. Retrospective data were collected with consecutive patients between January 2010 and March 2019 at Peking University Cancer Hospital based on the following criteria: (a) histologically proven CRC, (b) no prior treatment before 18F-FDG PET/CT scan, and (c) the presence of complete medical history and clinicopathological data. The exclusion criteria were (a) secondary malignant disease; (b) serious infection or inflammation; or (c) uncontrolled diabetes mellitus. Figure 1 shows the flowchart of selection criteria.

Fig. 1
figure 1

Flow diagram outlining criteria used for patient inclusion and exclusion

18F-FDG pet/CT

Whole-body acquisition was performed in 1–1.5 min/bed using a hybrid system (PHILIPS Gemini TF) that covered the area from the base of the skull to the upper thigh after intravenous injection of about 3.7 MBq/kg of 18F-FDG. All patients fasted for at least 6 h previously and presented with a blood glucose level lower than 10 mmol/L. Attenuation weighted ordered-subsets expectation maximization (AW-OSEM) iterative algorithm with 4 iterations and 8 subsets, Gaussian filter with 4.0 mm full width at half maximum (FWHM) and scatter correction were used for reconstruction [16].

Quantitative PET parameter computation

Maximum standardized uptake volume (SUVmax), mean SUV (SUVmean), metabolic tumor volume (MTV) and total lesion glycolysis (TLG) were calculated by selecting a Volume of Interest (VOI) in 3D mode using vendor-provided software at a PHILIPS EBW workstation. SUV(g/mL) = [measured activity concentration (Bq/mL)/ (injected activity [Bq]/body weight [kg] · 1000)], TLG(g) = SUVmean(g/mL) · MTV (cm3, [19]) (Units of these metabolic parameters are omitted for convenience below [20]). MTV was estimated for each primary CRC lesion with 40% of SUVmax as threshold and manual adjustment was applied when necessary to avoid nearby high physiologic uptake such as the bladder [21].

Immunohistochemistry

Immunohistochemistry was carried out in an automated tissue staining system (ImmunoVision Technologies, Brisbane, CA). Briefly, formalin-fixed, paraffin-embedded blocks were cut into 4-μm-thick sections, deparaffinized in xylene and rehydrated, which also used for histopathologic determinations and tumor-infiltrating lymphocytes (TIL). Antigen retrieval was performed using EDTA (pH 8.0; Santa Cruz Biochemistry, Dallas, TX) in a pressure cooker for 3 minutes. The sections were incubated in 3% H2O2 solution for 10 minutes at room temperature to block endogenous peroxidase activity.

IHC was conducted using antibody to hMLH1 (ready-to-use, clone GM002; GeneTech, Shanghai, CHINA), hMSH2 (ready-to-use, clone RED 2; GeneTech, Shanghai, CHINA), hMSH6 (ready-to-use, cloneEP49; GeneTech, Shanghai, CHINA), and hPMS2 (ready-to-use, clone EP51; GeneTech, Shanghai, CHINA), CD8 (Leica Biosystems PA0183, mouse clone 4B11, ready-to-use formulation), and CD3 (Leica NCL-L-CD3–565, mouse clone LN10, diluted 1:100). Tumors were designated as a high incidence of MSI when at least one out of the four markers showed instability [13]. Microsatellite stability (MSS) was defined when no loss of expression was observed for any of these markers. ≥ 30 lymphocytes per 100 epithelial cells were considered as intra-epithelial lymphocytosis [22]. All CRC diagnoses were provided by specialty-trained intestinal pathologists.

Statistical analysis

Statistical analysis was performed using SPSS software 23.0, (Inc.). Data are presented as median (range). Significant differences of variable characteristics between groups were compared by Mann-Whitney U-test for the continuous variables, and χ2 tests for the categorical variables. Receiver operating characteristic (ROC) curves were used to define optimal cut-off values for age, MTV and TLG using MedCalc software (Version 20.027). Logistic regression analysis was performed to determine the independent significant clinicopathological factors that showed a causal relationship with a dependent variable; a forward conditional method was used and the results are reported as hazard ratios (HR) and 95% confidence intervals (CI). Datasets were compared for patient demographic and clinical characteristics. P < 0.05 was considered statistically significant. Power analysis was performed using PASS software (Version 21.0.3).

Results

Patient characteristics

A total of 420 patients met our clinical and PET-based inclusion criteria and the details of clinicopathological characteristics are presented in Table 1. The mean age of CRC patients was 60 years (range 18–87 years), and 254 of these patients (60.5%) were men. The primary tumor was localized in the right hemi-colon in 118 (28.1%) patients, and moderately/highly differentiation was the most common histologic grade (approximately 85.9% of patients). The majority of patients were T2–3 (71.2%), N1–2 (58.6%) and M0 (79.3%) stage according to pathological results. On the basis of MSI status analysis of the primary tumor, 420 observational patients were classified into 2 groups: patient with MSI-H (44 patients, 10.5%) and MSS (376 patients, 89.5%). The median SUVmax, SUVmean, MTV and TLG values for the primary lesion were 13.775 (4.10–54.73), 7.93 (2.81–22.70), 18.56 (range 1.34–391.04) and 141.25 (range 5.36–2634.39), respectively.

Table 1 Clinical characteristics of patients

Clinicopathological findings and metabolic parameters according to the MSI status

The correlations between patient characteristics and MSI status are summarized in Table 2. More than half of the MSI-H CRC were located in the right (59.1%), whereas MSS CRC were found predominantly in the left hemi-colon (75.5%) (P < 0.001) (Fig. 2). And younger patients prone to encounter in MSI-positive CRC [56.5(24–84) vs 61(18–87); P = 0.048; Table 2, Fig. 2]. MSI-H colorectal cancers exhibited significantly higher MTV (33.60) and TLG (229.03) values of the primary lesion than MSS ones (18.08, and 134.26, respectively; P = 0.004 and 0.010, respectively) (Fig. 2). However, no significant differences between the MSI-H and MSS groups were found in terms of gender, histologic grade, TNM category and SUVs (Table 2).

Table 2 Correlations between patient characteristics and MSI status in CRC patients
Fig. 2
figure 2

A ROC curve of MTV for predicting MSI-H. Sensitivity and specificity were 52.3 and 76.6% (area under curve (AUC) value = 0.633; P = 0.004). B ROC curve of TLG for predicting MSI-H. Sensitivity and specificity were 43.2 and 80.9% (area under curve (AUC) value = 0.619; P = 0.010). C Correlation between Age and MSI status in CRC. Younger patients prone to encounter in MSI-positive CRC [56.5(24–84) vs. 61(18–87); P = 0.048]. D Correlation between primary lesion and MSI status in CRC. MSS were located predominantly in the left hemi-colon (75.5%), whereas more than half of the MSI-H colorectal cancers were found in the right (59.1%, P < 0.001). E Correlation between MTV and MSI status in CRC. MTV was significantly higher in tumors with MSI-H than in those with MSS (33.60 vs.18.08; P = 0.004). F Correlation between primary tumor TLG and MSI status in CRC. TLG was significantly higher in tumors with MSI-H than in those with MSS (229.03 vs. 134.26; P = 0.010)

HE-staining results showed intratumoral inflammatory cell infiltration, and the TIL in the MSI-H group was significantly higher than in the MSS group (Fig. 3). IHC staining of CRC lesion showed that CD8+ were resided in the tumor stroma and the tumor epithelium (Fig. 4). These results can suggest that MSI-H group had higher metabolic burden, possibly by increased density of TILs.

Fig. 3
figure 3

Representative pictures of intratumoral inflammatory cell infiltration by Hematoxylin-Eosin staining (× 20). A High density of inflammatory cell infiltration in MSI-H CRC. B Low density of inflammatory cell infiltration in MSS CRC

Fig. 4
figure 4

Representative Immunohistochemical detection of CD8 and CD3 (× 20) expression in slides of MSI-H CRC (A, B) and MSS CRC (C, D)

Predictive factors for the presence of microsatellite instability

We sought to determine the threshold of MTV and TLG for optimal differentiation between the MSI-H CRC group and the MSS CRC group. The optimal cut-off values of MTV and TLG were 32.19 (P = 0.004) and 352.72 (P = 0.010), respectively. Logistic analysis for microsatellite instability status revealed that right hemi-colon (HR 4.72, 95% CI 1.89–8.95; P < 0.001), age < 52y (HR 2.22, 95% CI 1.10–4.47; P = 0.026) and MTV ≥ 32.19 (HR 2.34, 95% CI 1.19–4.61; P = 0.014) were independent variables predicting MSI status (Table 3, Fig. 5).

Table 3 Logistic regression analysis for MSI in CRC patients
Fig. 5
figure 5

A a 45-year-old male had right colon cancer. 18F-FDG-PET/CT scans showed intense accumulation of 18F-FDG in the tumor (arrow; MTV,37.26; TLG,494.44). IHC analysis revealed MSI-H(MLH1(−) and PMS2(−)) after surgical resection. Scale bars, 100 mm. B a 55-year-old male had sigmoid colon cancer. 18F-FDG-PET/CT scans showed high accumulation of 18F-FDG in the tumor (arrow; MTV, 12.11; TLG,114.91). IHC analysis revealed MSS after surgical resection. Scale bars, 100 mm

Discussion

The most important contribution of this study is the evaluation of MSI status of primary CRC lesions with a set of metabolic parameters (SUV, MTV, and TLG) on 18F-FDG PET/CT imaging to guided personalized medicine. The strong predictive value of higher MTV, younger age and right hemi-colon could be confirmed with MSI-H CRC. This study demonstrated the significance of MSI status in detecting CRCs using PET/CT imaging.

CRC can be categorized into two discrete groups on the basis of mutation patterns: tumors that have an MSI signature with high overall mutation burden (> 12 mutations per 106 DNA bases) and tumors that have an MSS signature with a much lower mutation burden (< 8.24 mutations per 106 DNA bases) [23]. MSI-H CRCs, approximately 10–15% of all sporadic CRCs [24, 25], are more common in younger patients (< 50 years), right-sided and poorly differentiated stage 2 CRCs [26,27,28]. MSI-H colorectal cancers (CRCs) have been shown to have a better overall prognosis compared with MSS cancers [29]. There is also evidence that MS-H is one of these important molecular markers which not only associated with resistance to 5-fluorouracil (5-FU) based chemotherapy particularly in stage II patients but also predicts the response of CRC to PD-1 blockade [10, 29,30,31]. Several PD-1 blockades, such as pembrolizumab and nivolumab, were granted by FDA for adult and pediatric patients with unresectable or metastatic microsatellite instability–high (MSI-H) tumors. Thus, identifying potentially susceptible subgroups is important and necessary for applying immunotherapy in CRC patients.

In the present study, we have added another piece in the big puzzle of immunotherapy. Indeed, by using 18F-FDG PET/CT, we demonstrated and interesting association between MSI status and elevated metabolic tumor burden. This is different from a recent study of Chung and colleagues [18] in gastric cancer, exhibiting that MSI-H tumors caused higher SUVmax on18F-FDG PET/CT imaging, that may because gastric cancer with MSI-H tended to be larger-sized and histologically heterogeneous, which was different from colorectal cancer. We found a positive relationship between MSI status and MTV in colorectal cancer, which was in agreement with the previous findings [32]. Liu et al. [32] retrospectively analyzed the pretreatment parameters of PET and reported the highest diagnostic performance of MTV in predicting MSI status in CRC despite its small sample size of 50 patients. However, the specific mechanism behind the correlation between metabolic tumor burden and MSI status is still unknown. Numerous publications have identified histologic features and heterogeneity which are more commonly seen in MSI-H CRCs. MSI-H tumor have high level of CD3+ and CD8+ TILs and a prominent inflammatory reaction (Crohn-like reaction) at the advancing edge of the tumor [28, 33]. Arguably, a high level of somatic mutations often occurred in MSI-H tumors, generating multiple neopeptides and eliciting a robust host immune response associated with increased density of TILs and upregulation of immune checkpoint expression (including PD-1, PD-L1, and CTLA-4, [34, 35]. Upregulation of PD-L1 was reported to be linked to the activation of mitogen-activated protein-kinase (MARK) and phosphoinositide 3-kinase (PI3K) signaling pathways as well as the hypoxia-inducible factor-1α (HIF-1α), an essential factor contributing to the elevated FDG uptake [36]. In present study, we found MSI-H CRC had large tumor size with a circumscribed/expansile growth pattern. Histology results revealed abundant lymphocytes infiltrate CRC lesions by conventional H&E stain. Staining with antibodies against CD3 and CD8 revealed the presence of T cells both within and at the invasive margin of the tumor. Increased density of TILs, a prominent inflammatory reaction, and activated HIF-1α may explain that significantly higher MTV (33.60) and TLG (229.03), reflecting the number of cells with abnormal metabolism, of primary MSI-H CRC than MSS ones (18.08, and 134.26, respectively; P = 0.004 and 0.010, respectively) in present study.

18F-FDG PET may play a pivotal role in guiding ICI treatment since there is a strong rationale suggesting that abnormally increased glucose metabolism is a hallmark of cancer associated with tumor aggressiveness and immune response [37,38,39]. In this study, we reviewed 8 clinicopathological indicators and 4 metabolic parameters of 420 CRC patients and tried to explore their correlation with MSI status. We found approximately 10% of all CRC and 8% of mCRC with MSI-H, predominantly located in the right hemi-colon (59.1%) among younger people (age < 52) in our cohorts. This is in line with reported studies [27, 40,41,42]. These results may be of significance for patients who would like to receive PD-1/PD-L1 blockades but are unable or unwilling to undergo biopsy for MSI status testing, and provide reference value to the immunotherapy.

Despite these strengths, our study has some notable limitations. First, this was a single-centre study; therefore, a future large-scale multicentred study should be conducted to validate our results. Second, our cohort included mainly locally advanced or mCRC, and it remains unclear whether the conclusion can apply in early stage CRC patients. Finally, even though our study found 18F-FDG PET/CT may have good prediction performance, it cannot replace pathologic testing for examining MSI status. Nevertheless, our study has demonstrated that the 18F-FDG PET/CT metabolic parameters in combination with clinicopathologic features is clinically relevant for guiding therapeutic strategies in patients with CRC.

Conclusion

The MSI-H CRCs have higher MTV and younger age than the MSS types and mostly located in in the right hemi-colon in our large patient cohort. Our founding may serve as powerful indicators that identify patients with MSI status, those who cannot tolerate platinum-containing regiments but may benefit from immunotherapy such as anti-PD-1monoclonal antibody.

Availability of data and materials

The datasets used and/or analysed during the current study are available from the corresponding author on reasonable request.

Abbreviations

CRC:

Colorectal cancer

MSI-H:

Microsatellite instability high

18F-FDG PET/CT:

[18F]Fluorodeoxyglucose positron emission tomography/computed tomography

SUVmax :

Maximum standardized uptake value

SUVmean :

Mean standardized uptake value

MTV:

Metabolic tumor volume

TLG:

Total lesion glycolysis

References

  1. Bray F, Ferlay J, Soerjomataram I, Siegel RL, Torre LA, Jemal A. Global cancer statistics 2018: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries. CA Cancer J Clin. 2018;68(6):394–424.

    Article  PubMed  Google Scholar 

  2. Siegel RL, Miller KD, Fedewa SA, Ahnen DJ, Meester RGS, Barzi A, et al. Colorectal cancer statistics, 2017. CA Cancer J Clin. 2017;67(3):177–93.

    Article  PubMed  Google Scholar 

  3. Loupakis F, Cremolini C, Masi G, Lonardi S, Zagonel V, Salvatore L, et al. Initial therapy with FOLFOXIRI and bevacizumab for metastatic colorectal cancer. N Engl J Med. 2014;371(17):1609–18.

    Article  PubMed  CAS  Google Scholar 

  4. Franke AJ, Skelton WP, Starr JS, Parekh H, Lee JJ, Overman MJ, et al. Immunotherapy for colorectal Cancer: a review of current and novel therapeutic approaches. J Natl Cancer Inst. 2019;111(11):1131–41.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  5. De Roock W, Claes B, Bernasconi D, De Schutter J, Biesmans B, Fountzilas G, et al. Effects of KRAS, BRAF, NRAS, and PIK3CA mutations on the efficacy of cetuximab plus chemotherapy in chemotherapy-refractory metastatic colorectal cancer: a retrospective consortium analysis. Lancet Oncol. 2010;11(8):753–62.

    Article  PubMed  CAS  Google Scholar 

  6. Overman MJ, Lonardi S, Wong KYM, Lenz HJ, Gelsomino F, Aglietta M, et al. Durable clinical benefit with Nivolumab plus Ipilimumab in DNA mismatch repair-deficient/microsatellite instability-high metastatic colorectal Cancer. J Clin Oncol. 2018;36(8):773–9.

    Article  CAS  PubMed  Google Scholar 

  7. Price TJ, Thavaneswaran S, Burge M, Segelov E, Haller DG, Punt CJ, et al. Update on optimal treatment for metastatic colorectal cancer from the ACTG/AGITG expert meeting: ECCO 2015. Expert Rev Anticancer Ther. 2016;16(5):557–71.

    Article  CAS  PubMed  Google Scholar 

  8. Lemery S, Keegan P, Pazdur R. First FDA approval agnostic of Cancer site - when a biomarker defines the indication. N Engl J Med. 2017;377(15):1409–12.

    Article  PubMed  Google Scholar 

  9. Gelsomino F, Barbolini M, Spallanzani A, Pugliese G, Cascinu S. The evolving role of microsatellite instability in colorectal cancer: a review. Cancer Treat Rev. 2016;51:19–26.

    Article  CAS  PubMed  Google Scholar 

  10. Le DT, Uram JN, Wang H, Bartlett BR, Kemberling H, Eyring AD, et al. PD-1 blockade in tumors with mismatch-repair deficiency. N Engl J Med. 2015;372(26):2509–20.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  11. Overman MJ, McDermott R, Leach JL, Lonardi S, Lenz HJ, Morse MA, et al. Nivolumab in patients with metastatic DNA mismatch repair-deficient or microsatellite instability-high colorectal cancer (CheckMate 142): an open-label, multicentre, phase 2 study. Lancet Oncol. 2017;18(9):1182–91.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  12. De' Angelis GL, Bottarelli L, Azzoni C, De' Angelis N, Leandro G, Di Mario F, et al. Microsatellite instability in colorectal cancer. Acta bio-medica : Atenei Parmensis. 2018;89(9-s):97–101.

    CAS  Google Scholar 

  13. Evrard C, Tachon G, Randrian V, Karayan-Tapon L, Tougeron D. Microsatellite instability: diagnosis, heterogeneity, Discordance, and Clinical Impact in Colorectal Cancer. Cancers. 2019;11(10):1567.

    Article  CAS  PubMed Central  Google Scholar 

  14. Samstein RM, Chan TA. Dissecting microsatellite instability in colorectal cancer: one size does not fit all. Genome Med. 2017;9(1):45.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  15. Kleiner S, Weber W. Importance of FDG-PET/computed tomography in colorectal cancer. Radiologe. 2019;59(9):812–9.

    Article  CAS  PubMed  Google Scholar 

  16. Song J, Li Z, Chen P, Zhou N, Zhang Y, Yang Z, et al. The correlation between molecular pathological profiles and metabolic parameters of (18)F-FDG PET/CT in patients with gastroesophageal junction cancer. Abdom Radiol (NY). 2020;45(2):312–21.

    Article  Google Scholar 

  17. Kaira K, Shimizu K, Kitahara S, Yajima T, Atsumi J, Kosaka T, et al. 2-Deoxy-2-[fluorine-18] fluoro-d-glucose uptake on positron emission tomography is associated with programmed death ligand-1 expression in patients with pulmonary adenocarcinoma. Eur J Cancer. 2018;101:181–90.

    Article  CAS  PubMed  Google Scholar 

  18. Chung HW, Lee SY, Han HS, Park HS, Yang JH, Lee HH, et al. Gastric cancers with microsatellite instability exhibit high fluorodeoxyglucose uptake on positron emission tomography. Gastric Cancer. 2013;16(2):185–92.

    Article  PubMed  Google Scholar 

  19. Avallone A, Aloj L, Pecori B, Caracò C, De Stefano A, Tatangelo F, et al. (18)F-FDG PET/CT is an early predictor of pathologic tumor response and survival after preoperative Radiochemotherapy with bevacizumab in high-risk locally advanced rectal Cancer. J Nucl Med. 2019;60(11):1560–8.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  20. Zhang F, Wu X, Zhu J, Huang Y, Song X, Jiang L. 18F-FDG PET/CT and circulating tumor cells in treatment-naive patients with non-small-cell lung cancer. Eur J Nucl Med Mol Imaging. 2021;48(10):3250–9.

    Article  CAS  PubMed  Google Scholar 

  21. Im HJ, Bradshaw T, Solaiyappan M, Cho SY. Current methods to define metabolic tumor volume in positron emission tomography: which one is better? Nucl Med Mol Imaging. 2018;52(1):5–15.

    Article  PubMed  Google Scholar 

  22. Veress B, Franzén L, Bodin L, Borch K. Duodenal intraepithelial lymphocyte-count revisited. Scand J Gastroenterol. 2004;39(2):138–44.

    Article  CAS  PubMed  Google Scholar 

  23. Sveen A, Kopetz S, Lothe RA. Biomarker-guided therapy for colorectal cancer: strength in complexity. Nat Rev Clin Oncol. 2020;17(1):11–32.

    Article  PubMed  Google Scholar 

  24. Tariq K, Ghias K. Colorectal cancer carcinogenesis: a review of mechanisms. Cancer Biol Med. 2016;13(1):120–35.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  25. Zang YS, Dai C, Xu X, Cai X, Wang G, Wei J, et al. Comprehensive analysis of potential immunotherapy genomic biomarkers in 1000 Chinese patients with cancer. Cancer Med. 2019;8(10):4699–708.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  26. Shia J, Ellis NA, Paty PB, Nash GM, Qin J, Offit K, et al. Value of histopathology in predicting microsatellite instability in hereditary nonpolyposis colorectal cancer and sporadic colorectal cancer. Am J Surg Pathol. 2003;27(11):1407–17.

    Article  PubMed  Google Scholar 

  27. Kanno H, Miyoshi H, Yoshida N, Sudo T, Nakashima K, Takeuchi M, et al. Differences in the immunosurveillance pattern associated with DNA mismatch repair status between right-sided and left-sided colorectal cancer. Cancer Sci. 2020;111(8):3032–44.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  28. Greenson JK, Huang SC, Herron C, Moreno V, Bonner JD, Tomsho LP, et al. Pathologic predictors of microsatellite instability in colorectal cancer. Am J Surg Pathol. 2009;33(1):126–33.

    Article  PubMed  PubMed Central  Google Scholar 

  29. Sinicrope FA, Foster NR, Thibodeau SN, Marsoni S, Monges G, Labianca R, et al. DNA mismatch repair status and colon cancer recurrence and survival in clinical trials of 5-fluorouracil-based adjuvant therapy. J Natl Cancer Inst. 2011;103(11):863–75.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  30. Carethers JM, Smith EJ, Behling CA, Nguyen L, Tajima A, Doctolero RT, et al. Use of 5-fluorouracil and survival in patients with microsatellite-unstable colorectal cancer. Gastroenterology. 2004;126(2):394–401.

    Article  CAS  PubMed  Google Scholar 

  31. Ribic CM, Sargent DJ, Moore MJ, Thibodeau SN, French AJ, Goldberg RM, et al. Tumor microsatellite-instability status as a predictor of benefit from fluorouracil-based adjuvant chemotherapy for colon cancer. N Engl J Med. 2003;349(3):247–57.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  32. Liu H, Ye Z, Yang T, Xie H, Duan T, Li M, et al. Predictive value of metabolic parameters derived from (18)F-FDG PET/CT for microsatellite instability in patients with colorectal carcinoma. Front Immunol. 2021;12:724464.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  33. Jenkins MA, Hayashi S, O'Shea AM, Burgart LJ, Smyrk TC, Shimizu D, et al. Pathology features in Bethesda guidelines predict colorectal cancer microsatellite instability: a population-based study. Gastroenterology. 2007;133(1):48–56.

    Article  CAS  PubMed  Google Scholar 

  34. Bever KM, Le DT. An expanding role for immunotherapy in colorectal Cancer. J Natl Compr Canc Netw. 2017;15(3):401–10.

    Article  CAS  PubMed  Google Scholar 

  35. Galon J, Costes A, Sanchez-Cabo F, Kirilovsky A, Mlecnik B, Lagorce-Pagès C, et al. Type, density, and location of immune cells within human colorectal tumors predict clinical outcome. Science (New York, NY). 2006;313(5795):1960–4.

    Article  CAS  Google Scholar 

  36. Noman MZ, Desantis G, Janji B, Hasmim M, Karray S, Dessen P, et al. PD-L1 is a novel direct target of HIF-1α, and its blockade under hypoxia enhanced MDSC-mediated T cell activation. J Exp Med. 2014;211(5):781–90.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  37. Rossi S, Toschi L, Castello A, Grizzi F, Mansi L, Lopci E. Clinical characteristics of patient selection and imaging predictors of outcome in solid tumors treated with checkpoint-inhibitors. Eur J Nucl Med Mol Imaging. 2017;44(13):2310–25.

    Article  CAS  PubMed  Google Scholar 

  38. Seban RD, Moya-Plana A, Antonios L, Yeh R, Marabelle A, Deutsch E, et al. Prognostic 18F-FDG PET biomarkers in metastatic mucosal and cutaneous melanoma treated with immune checkpoint inhibitors targeting PD-1 and CTLA-4. Eur J Nucl Med Mol Imaging. 2020;47(10):2301–12.

    Article  CAS  PubMed  Google Scholar 

  39. Kuriyama K, Higuchi T, Yokobori T, Saito H, Yoshida T, Hara K, et al. Uptake of positron emission tomography tracers reflects the tumor immune status in esophageal squamous cell carcinoma. Cancer Sci. 2020;111(6):1969–78.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  40. André T, de Gramont A, Vernerey D, Chibaudel B, Bonnetain F, Tijeras-Raballand A, et al. Adjuvant fluorouracil, Leucovorin, and Oxaliplatin in stage II to III Colon Cancer: updated 10-year survival and outcomes according to BRAF mutation and mismatch repair status of the MOSAIC study. J Clin Oncol. 2015;33(35):4176–87.

    Article  PubMed  CAS  Google Scholar 

  41. Lynch HT, de la Chapelle A. Hereditary colorectal cancer. N Engl J Med. 2003;348(10):919–32.

    Article  CAS  PubMed  Google Scholar 

  42. Samowitz WS. Evaluation of colorectal cancers for Lynch syndrome: practical molecular diagnostics for surgical pathologists. Modern pathology : an official journal of the United States and Canadian academy of pathology. Inc. 2015;28(Suppl 1):S109–13.

    Google Scholar 

Download references

Acknowledgements

Not applicable.

Funding

This work was supported by National Natural Science Foundation of China (82071957), Beijing Hospitals Authority Clinical Medicine Development of Special Funding Support (XMLX202120) and Zhejiang Province Public Welfare Technology Application Research Project (LGF22H180013).

Author information

Authors and Affiliations

Authors

Contributions

ZWL and LJY analyzed pathologic data and immunohistochemical results. ZY mainly took charge of quality control of PET imaging. JLS, the first author, collecting, analyzed and interpreted PET data; drafted the manuscript. MMW, master student, collecting clinical data and follow-up CRC patients. XJW, the corresponding author, responsible for the study designing, and obtaining grants and funding to support the trial; revised the manuscript and enhanced the intellectual content of the manuscript. All authors read and approved the final manuscript.

Corresponding author

Correspondence to Xuejuan Wang.

Ethics declarations

Ethics approval and consent to participate

This retrospective chart review study involving human participants was in accordance with the ethical standards of the institutional and national research committee and with the 1964 Helsinki Declaration and its later amendments or comparable ethical standards. The Investigational Review Board of Peking University Cancer Hospital approved this study (IRB number: 2022YJZ48). The requirement to acquire informed consent was waived owing to the Ethics Committee of Peking University Cancer Hospital.

Consent for publication

Not applicable.

Competing interests

The authors declare that they have no competing interests.

Additional information

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Song, J., Li, Z., Yang, L. et al. Metabolic activity via 18F-FDG PET/CT is predictive of microsatellite instability status in colorectal cancer. BMC Cancer 22, 808 (2022). https://doi.org/10.1186/s12885-022-09871-z

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1186/s12885-022-09871-z

Keywords