Results

Overview of included studies

Study selection

The complete screening process is outlined in the PRISMA 2020 flow diagram (Fig. 1). The initial literature search yielded 5961 records. After deduplication, 4190 titles and abstracts were screened, leading to 178 full-text assessments. An updated search identified 2839 additional records, of which 79 were reviewed in full-text, resulting in a total 266 articles undergoing full-text evaluation. Most excluded studies were prognostic or predictive in nature (n = 42), lacking clear definitions of cases and controls (n = 40), or not meeting inclusion criteria for amino acids (n = 33). Additional exclusions were made for studies addressing alternative comparisons (n = 27), language/access issues (n = 5), non-primary research or insufficient data (n = 9), non-human studies (n = 5), and unclear outcomes due to unreported amino acid changes (n = 3). The targeted screening of PubMed did not identify any additional eligible studies that substantially affected the results or conclusions of the present review. In total, 77 articles were included in this systematic review.

Fig. 1: Preferred reporting items for systematic reviews and meta-analyses (PRISMA) flow diagram. CENTRAL Cochrane Central Register of Controlled Trials

Study characteristics

Details on study characteristics are summarized in Table 1. A total of 77 studies published between 1996 and 2025 were included in this review. The majority were case–control studies, alongside a smaller number of cross-sectional cohort designs. Most studies were conducted in China (n = 35), followed by European countries (n = 15), Japan (n = 8), the United States (n = 7), and South Korea (n = 3). Fewer studies were conducted in Singapore (n = 3), Canada (n = 3), and Iran, Egypt, Nigeria, and Turkey (each n = 1). All studies involved adults with colorectal cancer (77 studies; total CRC cases = 6263), with the number of cases per study ranging from 8 to 437. Six studies included individuals with advanced adenomas (n = 351), with sample sizes ranging from 10 to 159. A total of 56 studies included a healthy control group (n = 6283), with the number of controls per study ranging from 3 to 995. No studies were identified that included adults with advanced serrated polyps. Various biological matrices were described across the included studies, including faeces (n = 18), urine (n = 8), serum (n = 20), plasma (n = 8), tissue (n = 23), saliva (n = 1), serum-derived exosomes (n = 1), and microbiome-derived vesicles (n = 1). Three main categories of analytical techniques were employed across the included studies: mass spectrometry-based approaches (n = 61), nuclear magnetic resonance (NMR) spectroscopy (n = 16), and high-performance liquid chromatography (HPLC; n = 2). Among the mass spectrometry-based methods, liquid chromatography–mass spectrometry (LC–MS/MS; n = 35) and gas chromatography–mass spectrometry (GC–MS; n = 19) were most frequently used, followed by capillary electrophoresis–mass spectrometry (CE-MS; n = 4), flow injection analysis–tandem mass spectrometry (FIA-MS/MS; n = 2), and time-of-flight secondary ion mass spectrometry (TOF–SIMS; n = 1) (Fig. 2). Supplementary Table 3 provides an overview of the distribution of primary analytical methods across different matrices and their frequency of use in targeted versus untargeted studies. Although all included methods were classified under these overarching categories, a range of analytical variants was applied, differing in aspects such as instrumentation and the use of commercial kits. Details of specific analytical configurations and instrumentation are provided in Supplementary Tables 4–6.

Author [year] refs | Study design, country | Study group | number | Gender, m/f | Age (y) | Diagnosis (case|control) | CRC TNM stage (n) | Matrix
0|I|II|III|IV | 
Bosch, S. [2022] [14] | Case–control study, the Netherlands | CRC|AA|Ctrl | 12|10|20 | 6/6|9/1|14/6 | 67 [60–71]|71 [70–73]|67 [62–75] b | C|C | no data | Faeces
Coker, O. [2022] [10] | Cross-sectional cohort study, China | CRC|Ctrl | 118|128 | 64/54|59/69 | 73.21 ± 10.37|64.03 ± 6.84 c | C|C | no data | Faeces
Du, X. [2022] [28] | Case–control, China | CRC|Ctrl | 30|33 | 12/18|13/20 | 56.67|59.27 c | C|C | 0|2|12|14|2 | Faeces
Erben, V. [2021] [22] | Cross-sectional cohort study, Germany | CRC + AA|Ctrl | 12 + 159|229 | 103/68|123/106 | 61.1 ± 8.6|60.9 ± 8.0 c | C|C | no data | Faeces, urine and plasma
Kim, M. [2020] 20 | Case–control, USA | AA|Ctrl | 102|102 | 62/40|62|40 | 50-59y 17, 60-69y 50, > 70y 35 | 50-59y 18, 60-69y 49, > 70y 35 | C|C | no data | Faeces
Kong, C. [2022] [41] | Case–control, China | LO-CRC|Ctrl | 130|97 | 81/49|42/55 | 62.32 ± 7.96 | 61.56 ± 7.35 c | C|C | 0 + I 18|46|52|14 | Faeces
EO-CRC|Ctrl | 114|100 | 57/57|47/53 | 39.96 ± 7.01 |39.00 ± 7.31 c | 0 + I 15|28|49|22
Kulecka, M. [2024] [53] | Case–control, Poland | CRC|Ctrl | 40|40 | 20/20|20/20 | ♀: 66[36–82], ♂:67[35–82] | ♀: 68[49–79], ♂:61[50–81] | C|Screening | no data | Faeces
Le Gall, G. [2018] [54] | Case–control, UK | Set 1: CRC|Ctrl | 20|20 | 12/8|12/8 | 67[61–72]|67[60–74] c | C|C | Duke 3 A, 7B, 5C | Faeces
Set 2: CRC|Ctrl | 30|29 | 21/9|21/9 | 66[60–74]|66[60–74] c | Duke 3 A, 2B, 11C
Liang, L. [2024] [40] | Case–control, China | RCC|LCC|Ctrl | 63|79|88 | no data | no data | C|C | no data | Faeces
Lin, Y. [2019] [55] | Case–control, China | CRC|Ctrl | 50|50 | sex matched, no data | age matched, no data | C|ME | no data | Faeces
CRC|DNT|ANT | 70 | no data | no data | H | No data | Tissue
Lin, Y. [2016] [24] | Case–control, China | CRC|Ctrl | 68|32 | 36/32|15/17 | 56 ± 21|57 ± 23 | H|ME | 0|I + II 20|25|23 | Faeces
Monleon, D.[2009] [56] | Case–control, Spain | CRC|Ctrl | 21|11 | 7/14|2/9 | 65[32–79]|59[31–59)] b | C|C | no data | Faeces
Ramzy, A. [2025] [57] | Case–control, Egypt | CRC|Ctrl | 20|20 | 20/0|20/0 | 53.9 ± 4.8|53.5 ± 3.7 | C|BT/C/I | 0|2|1|4|3 | Faeces
Sun, X. [2020] [58] | Case–control, China | CRC|Ctrl | 46|38 | 32/14|24/14 | 63.63 ± 11.39|6.85 ± 10.99 c | C|C | no data | Faeces
Telleria, O. [2022] [19] | Case–control, Spain | CRC|AA|Ctrl | 40|40|40 | 20/20|20/20|20/20 | 69[38–91]|71[53–86]|76[40–88] b | C|C | no data | Faeces
Yachida, S. [2019] [2] | Cross-Sectional Cohort Study, Japan | CRC|AA|Ctrl | 148|30|149 | 88/60|15/15|86/63 | I + II 63.58 ± 8.84, III + IV 59.5 ± 11.46|63.73 ± 8.77 | 64.11 ± 10.9 | C|C | 30|51|29|44|24 | Faeces
Yang, Y. [2019] [59] | Case–control, China | CRC|Ctrl | 50|50 | 26/24|17/33 | < 60y: 14, > 60: 36|< 60: 20, > 60: 30 | C|C | 2|9|13|16|10 | Faeces
Zhang, Q. [2024] [60] | Cross-Sectional Cohort Study, China | CRC|Ctrl | 245|244 | 153/92|107/137 | 54.10 ± 13.23|49.94 ± 13.56 c | C|C | 0|I + II 123|III-IV 121 | Faeces
Kim, D. [2020] [15] | Case–control, Korea | CRC|Ctrl | 32|40 | 20/12|22/18 | 64[45–80]|64.5[49–78] c | C|ME | 1|7|12|9|3 | MEV
Yagin, F. d [2023] [61]
Deng, L. [2019] [62] | Case–control study, Canada | CRC-CAD|CRC-MSKCC|Ctrl | 121|50|171 | 68/59|24/26|100/71 | 67.4 ± 10.9|63.8 ± 12.5|58.9 ± 5.6 c | C|C|C | CAD: 3|16|30|51|21 | Urine
MSKCC: 0|14|20|6|10
Deng, Y. [2020] [16] | Case–control study, China | CRC|Ctrl | 139|50 | 91/48|28/22 | 63[36–87]|61[47–89] b | H|ME | 8|26|42|50|13 | Urine
Deng, W. [2024] [11] | Case–control study, China | CRC|Ctrl | 155|115 | 63/52|145/10 | 64|46 b | H|ME | 0|14|31|48|22 | Urine
Kim, E. [2019] [23] | Case–control study, Korea | CRC|AA|Ctrl | 24|36|156 | no data|76/80 | no data|52 [22–76] b | C|C | 24|0|0|0|0 | Urine
Ning, W. [2021] [17] | Case–control study, China | CRC|Ctrl | 163|111 | 103/60|69/42 | 66 < 60, 97 > 60,|61 < 60, 50 > 60 | C|ME | 0 | 0 | 65 | 74 | 24 | Urine
Wang, Z. [2017] [18] | Case–control study, China | CRC|Ctrl | 23|40 | 11/12|19/21 | 61[27–84]|59[28–78] b | C|NHC + no GI symptoms | only stage I and II | Urine
Zhang, L. [2023] [63] | Cross-sectional cohort study, Nigeria | CRC|Ctrl | 169|194 | 95/74|125/69 | 55[19–73]|56[21–74] b | C|C | No data | Urine
Bednarz-Misa, I. [2020] [32] | Case–control, Poland | CRC|Ctrl | 137|54 | 72/65|24/30 | 63.6 ± 10.9|60.5 ± 13 c | C|ME/BT | 5|17|52|46|17 | Serum
Deng, L. [2016] [64] | Cross-sectional cohort study, USA | CRC|Ctrl | 28|55 | 16/12|25/30 | 55.3[27–86]|52.8[21–74] c | C|C | 0|I + II 3|8|17 | Serum
Farshidfar, F. [2016] [65] | Case–control, Canada | CRC|Ctrl | 320|254 | 201/119|148/106 | I 68.6 ± 10.6, II 68.6 ± 12.4, III 64.9 ± 13.1, IV 63.1 ± 11.5| 61.7 ± 9.3 c | C|C | 0|47|60|71|142 | Serum
Farshidfar, F. [2018] [66] | Case–control, Canada | CRC|Ctrl | 62|81 | 46/16|58/23 | I 76.9 ± 6.1, II 67.3 ± 9.8, III 62.8 ± 14.8, IV 60.5 ± 9.9 | 60.5 ± 6.7 c | C|C | 0|8|8|8|38 | Serum
Gu, J. [2019] [67] | Case–control, China | CRC|Ctrl | 40|38 | 27/13|21/17 | 60[25–82]|55[35–77] b | C|C | 0|7|9|14|14 | Serum
Guo, J. [2023] [68] | Case–control, China | CRC|Ctrl | 8|14 | 4/4|7/7 | 46.9 ± 7.7|43.4 ± 6.1 c | C|C | no data | Serum
Huang, H. [2002] [69] | Case–control, UK | CRC|Ctrl | 66|37 | 39/27|13/27 | 66[61–73]|69[64–74] e | C|NHC | no data | Serum
Ikeda, A. [2011] [70] | Case–control, Japan | CRC|Ctrl | 12|12 | 8/4|5/7 | 71.3[63–83]|58.5[45–74] b | C|BT/C/I | 0|3|4|5|0 | Serum
Leichtle, A. [2012] [29] | Case–control, Germany | CRC|Ctrl | 59|58 | 37/22|26/32 | 59 [45–90]|58 [38–75] b | C|BT/ME | 0|5|20|16 | Serum
Li, J. [2019] [12] | Case–control, China | Screening: CRC|Ctrl | 120|120 | 73/47|73/47 | 63.1 ± 13.1|61.7 ± 12.2 c | H|ME | 0|11|35|62|12 | Serum
Validation: CRC|Ctrl | 437|580 | 252/185|298/282 | 59.1 ± 12.5|58.1 ± 11.4 | 0|76|126|153|82
Long, Y. [2017] [71] | Case–control, China | CRC | Ctrl | 30|30 | 18/12|18/12 | 53.97 ± 13.46|55.23 ± 10.46 c | H|NHC | 0|I + II 20|25|23 | Serum
Nishiumi, S. [2012] [27] | Case–control, Japan | Training: CRC|Ctrl | 60|60 | 39/21|39/21 | 67.7[36–88]|64.5[39–88] c | H|BT/C/I | 12|12|12|12|12 | Serum
Validation: CRC|Ctrl | 59|63 | 30/29|32/31 | 64.8[31–84]|62.8[47–73] c | 15|11|3|11|19 | Serum
Qiu, Y. [2009] [72] | Case–control, China | CRC|Ctrl | 64|65 | 35/29|34/31 | 59[42–74]|55[42–69] b | H|ME | 0|9|27|20|8 | Serum
Tan, B. [2013] [73] | Case–control, China | CRC|Ctrl | 62|62 | 34/28|28/34 | 60.1 [24 − 82]|59.4 [31 − 75] c | C|ME | 0|16|25|17|4 | Serum
Tevini, J. [2022] [21] | Case–control, Austria | Training: CRC|AA|Ctrl | 18|28|36 | 11/7|14/14|18/18 | 67 ± 12|60 ± 10|53 ± 8 | C|C | no data | Serum
Validation: CRC|Ctrl | 48|29 | 31/17|3/26 | 69 ± 10|68 ± 7
Validation: AA|Ctrl | 48|28 | 26/22|28/0 | 66 ± 10|66 ± 5
Tristán, A. [2023] [26] | Case–control, Spain | CRC|Ctrl | 57|26 | 29/28|14/12 | 60.0 ± 5.33|65.5 ± 6.83 c | C|ME | 0|0|0|0|57 | Serum
Uchiyama, K. [2017] [39] | Case–control, Japan | CRC|Ctrl | 56|60 | 25/28|30/30 | I 70.4 ± 8.2, II 69.3 ± 9.6, IIIa 71 ± 6.7, IIIb 71.3 ± 10.4, IV 70.7 ± 10|67.7 ± 9.2 c | C|C | 0|14|14|14|14 | Serum
Wu, J. [2020] [74] | Case–control, China | CC|RC|Ctrl | 22|23|45 | 15/7|16/7|31/14 | 66.49[49–84]|64.41[49–84]|68.48[54–80]c | C|BT | no data | Serum
Zhu, J. [2014] [75] | Cross-sectional cohort study, USA | CRC|Ctrl | 66|92 | 30/36|45/47 | 58[27–88]|57[18–80] b | C|C | 0|I + II 21|17|28 | Serum
Eylem, C. [2020] [76] | Case–control, Turkey | CRC|Ctrl | 8|8 | 6/2|no data | 56.5[53–71]|no data b | H|ME | 0|2|2|1|3 | Serum exosomes
Coradduzza, D. [2022] [77] | Case–control, Italy | CRC|Ctrl | 50|52 | 33/17|no data | 7.74 ± 10.44|55.42 ± 5.14 c | H|ME | 1|10|13|17|7|2 | Plasma
Geijsen, A. [2019] [78] | Case–control, Germany + Austria | Discovery: CRC|Ctrl | 180|153 | 114/66|59/94 | 66.0[58.0–73.0]|51.0[42.0–63.0] e | H|NHC | 7|34|66|47|25 | Plasma
Replication: CRC|Ctrl | 88|200 | 60/28|130/70 | 70.0[60.0–76.0]|64.0[57.0–74.0] e | 0|30|17|18|12
Miyagi, Y. [2011] [30] | Case–control, Japan | CRC|Ctrl | 199|995 | 126/73|570/425 | CRC 63.7 ± 9.5|62.4 ± 9.5 c | C|ME | 8 | 63 | 48 | 59 | 19 | Plasma
Nishiumi, S. [2017] [31] | Case–control, Japan | CRC|Ctrl | 282|291 | 170/112|178/113 | 67 ± 9.02|66.8 ± 7.94 c | C|CRC screening | 79|80|123|0|0 | Plasma
Okamoto, N.[2009] [79] | Case–control, Japan | CRC|Ctrl | 103|62 | 42/20|52/51 | 62.7 ± 9.5|57.6 ± 6.1 c | H|ME | 2|9|22|22|6 | Plasma
Rodriguez-Tomas, E. [2021] [80] | Case–control, Spain | RC|Ctrl | 32|48 | 19/29|22/10 | 67.7 ± 9.5|41.9 ± 10.0 c | H|ME | 0|0|5|27|0 | Plasma
Sun, Y. [2024] [81] | Case–control, China | CRC|Ctrl | 111|119 | 64/47|52/67 | 61.90 ± 11.49|43.76 ± 11.60 | C|C | 3|21|17|36|18 | Plasma
Arima, K. [2020] [82] | Case–control, paired, USA | CRC + paired normal | 11 | no data | no data | H | no data | Tissue
Cai, Y. [2020] [83] | Case–control, USA | CRC|normal f | 39|39 | 20/19|27/12 | 69.5 ± 8.5|67.4 ± 12.4 c | H | 0|13|14|12|0 | Tissue
Cai, R. [2025] [84] | Case–control, paired, China | CRC + paired normal | 106 | 51/55 | < 60: 44|≥ 60: 62 | H | 0|6|19|43|32 | Tissue
Chan, E. [2009] [85] | Case–control, paired, Singapore | CRC + paired normal | 31 | 18/13 | 67 ± 13 c | H | 0|3|10|13|5 | Tissue
Cho, K. [2021] [86] | Case–control, paired, Korea | CRC + paired normal | 90 | 45/45 | no data | H | no data | Tissue
Denkert, C. [2008] [87] | Case–control, Germany | CRC|Ctrl g | 27|18 | 12/15 | no data | H | 0|3|9|14|1 | Tissue
Feizi, H. [2025] [88] | Case–control, Iran | CRC|Ctrl | 14|20 | 7/7|10/10 | 40-49y 2, 50-59y 1, 60-69y 4, 70-79y 7 | 40-49y 2, 50-59y 4, 60-69y 6, 70-79y 8 | H|H | no data | Tissue
Gao, P. [2016] [89] | Case–control, China | CRC + paired normal | 11 | no data | no data | H | no data | Tissue
Jiménez, B. [2013] [90] | Case–control, UK | CRC + paired normal | 83|87 h | 10/16 | 72[26–87] b | H | 0|2|10|14|0 | Tissue
Kinross, J. [2017] [91] | Case–control, paired, UK | CRC + paired normal | 18 | 10/8 | 76[55–85] b | H | No data | Tissue
Long, Z. [2020] [92] | Case–control, paired, China | CRC + paired normal | 51 | 24/26 | 57[22–79] b | H | 0|4|21|15|4 | Tissue
Lv, W. [2020] [93] | Case–control, paired, China | CRC|DNT|ANT | 22 | 13/9 | ♂ 64.46 ± 3.49, ♀ 60.44 ± 4.00 c | H | No data | Tissue
Mal, M. [2012] [94] | Case–control, paired, Singapore | CRC + paired normal | 31 | 18/13 | 67 ± 13 c | H | 0|4|10|13|5 | Tissue
Manna, S. [2014] [95] | Case–control, paired, USA | CRC + paired normal | 39 | 19/20 | 69 ± 15.3 b | H | 0|I + II 21|III + IV 18 | Tissue
Moreno, A. [1996] [96] | Case–control, partly paired, Spain | CRC + paired normal | 16|10 | 11/5 | 65 ± 11 c | H | 0|5|4|6|1 | Tissue
Ning, W. [2017] [25] | Case–control, paired, China | CRC + paired normal | 20 | 13/7 | 8 < 60 years 12 > 60 years | H | 0|0|8|9|3 | Tissue
Phua, L.C. [2014] [97] | Case–control, paired, Singapore | CRC + paired normal | 11 | 7/4 | 64.5[56–80] c | H | 0|0|6|5|0 | Tissue
Qiu, Y. [2014] [98] | Case–control, USA + China | [Set 1] CRC + partly paired normal | 85|55 | 49/36 | 57[31–79] b | H | 0|7|35|37|6 | Tissue
[Set 2] CRC + paired normal | 23 | 10/13 | 61[40–75] b | 0|3|9|10|1
[Set 3] CRC + paired normal | 65 | 43/22 | 61[34–84] b | 0|11|22|21|11
[Set 4] CRC + paired normal | 29|27 | 8/12 | 59[35–81] b | 1|2|2|14|1
Rao, J. [2024] [99] | Case–control, paired, China | CRC + paired normal | 10 | 8/2 | 65[34–85] b | H | 0|1|2|6|1 | Tissue
Wang, H. [2013] [100] | Case–control, partly paired, China | RC|Ctrl i | 127|43 | 69/58|16/27 | 55[28–86]|56[35–85] e | H | 0|35|37|37|18 | Tissue
Wang, Q. [2020] [101] | Case–control, paired, China | CRC + paired normal | 17 | No data | No data | H | No data | Tissue
Zha, H. [2018] [102] | Case–control, paired, China | CRC + paired normal | 18 | 9/9 | 61.35 ± 9.52 2 | H | No data | Tissue
Su, H. [2025] [103] | Case–control, China | CRC|Ctrl | 35|36 | 15/20|15/21 | 51.51 ± 11.47|41.39 ± 7.41 c | C|C | 0|7|12|10|6 | Saliva

Fig. 2: Distribution of analytical techniques used for amino acid measurement. Pie chart illustrating the distribution of analytical methods applied across the included studies. A detailed breakdown of mass spectrometry-based techniques is provided in the adjacent inset. The number following each technique indicates the number of studies that employed the respective method. The total number of methods exceeds the number of included studies, as two studies employed two distinct analytical approaches. CE-MS Capillary Electrophoresis–Mass Spectrometry; FIA-MS/MS Flow Injection; Analysis–Tandem Mass Spectrometry; GC–MS Gas Chromatography–Mass Spectrometry; HPLC High-Performance Liquid Chromatography; LC–MS/MS Liquid Chromatography–Tandem Mass Spectrometry; NMR spectroscopy Nuclear Magnetic Resonance Spectroscopy; TOF–SIMS Time-of-Flight Secondary Ion Mass Spectrometry

Quality assessment

The NOS was applied to 70 case–control studies and seven cross-sectional studies (Supplementary Tables 7 and 8). In most studies, cases were clearly defined and diagnosed using colonoscopy. However, in 13 studies (17%), while CRC or polyps were confirmed endoscopically, the histological classification was incomplete, with unclear distinction between advanced and non-advanced adenomas, or between adenomas and serrated polyps. Therefore, only the CRC versus control comparison in these studies was included in the present review. In 27 case–control studies (39%), controls were not colonoscopy-confirmed but identified based on alternative criteria, including absence of symptoms, normal clinical assessment, or lack of cancer history (Table 1). Although this introduces a potential risk of undetected lesions, these individuals were considered sufficiently low-risk to be included in CRC versus control comparisons. Fifty-four studies (70%) adjusted for age, and 51 studies (66%) for additional confounders including, sex, BMI, ethnicity, or smoking status. Metabolomic and amino acid analyses were consistently performed between cases and controls. Exclusion criteria were clearly reported in all studies, however, no study met the NOS non-response criterium. Overall, methodological quality ranged from 6 to 8 of 9 stars.

Differential amino acid profiles

Amino acid profiles in colorectal cancer versus controls

Supplementary Table 4 summarises the full study findings for the CRC versus controls comparison. A total of 17 studies investigated faecal amino acid profiles, encompassing 21 cohorts (CRC patients: n = 1335; controls: n = 1170). The majority of studies (12 out of 17; 71%) employed mass spectrometry, including LC–MS (n = 7), GC–MS (n = 4), and CE–MS (n = 1). Additionally, four studies (24%) used NMR spectroscopy, and one study applied HPLC. For nearly all amino acids, most studies found no significant differences in faecal concentrations between CRC patients and controls. Nonetheless, with the exception of four amino acids, at least one study per metabolite report a significant increase in CRC, particularly for alanine, phenylalanine, and proline (≥ 5 studies) (Fig. 3a, Supplementary Table 4). Nine amino acids were reported as significantly decreased in CRC patients in some studies, however, non-significant findings were more common across the literature. Due to these inconsistencies, no clear CRC-specific faecal amino acid pattern could be identified. This lack of consistency persisted when we analysed targeted and untargeted studies separately, with most studies again reporting non-significant differences (Supplementary Fig. 1a). One untargeted study specifically analysed microbial extracellular vesicles (MEVs) isolated from faeces and identified elevated levels of leucine, isoleucine, alanine, and lysine in CRC patients, which partly align with results from faecal studies [15].

Fig. 3: Directional changes in amino acid concentrations across matrices and comparisons, based on both targeted and untargeted approaches. Panels show results for a CRC versus controls, b advanced adenoma patients versus controls, and c advanced neoplasia patients versus controls. For each comparison, a matrix-specific summary is shown for the 20 amino acids included in this review. The Y-axis lists the amino acids; the X-axis indicates the biological matrices. Each circle reflects the number of studies reporting a significant increase (red), decrease (blue), or no significant difference (ND, grey) in amino acid levels. Circle size corresponds to the number of studies, with larger circles indicating greater consistency. Numbers within the circles denote how many studies reported the respective outcome out of the total number of studies assessing that amino acid in that matrix. Deng et al. (2024) reported L- and D-enantiomers separately; only amino acids showing significant changes in both forms were included for consistency

Serum amino acid profiles showed a similar degree of inconsistency as observed in faecal samples. However, amino acids in serum were more frequently found to be in CRC patients. In total, 20 studies investigated serum samples, encompassing 28 cohorts (CRC patients: n = 1764; controls: n = 1750). Mass spectrometry was the most commonly used analytical technique, applied in 18 of the 20 studies (90%), including LC–MS (n = 8), GC–MS (n = 7), FIA-MS (n = 2) and CE–MS (n = 1). NMR spectroscopy was used in three studies (15%), while one study employed HPLC. For each of the 20 amino acids, at least one study reported reduced concentrations in CRC. Alanine, histidine, lysine, proline, tryptophan, and tyrosine were more often found to be downregulated than non-differential, although the difference was marginal. For 16 amino acids, increased levels were also described; glutamate and isoleucine were elevated in six studies, whereas seven other studies found no significant difference for these same metabolites. When analysing targeted and untargeted studies separately overall patterns remained largely consistent (Supplementary Fig. 1). However, targeted studies more frequently identified elevated levels of aspartic acid, glutamate, and isoleucine. In contrast, amino acids that were more commonly downregulated overall, including alanine, lysine, proline, tryptophan, and tyrosine, were more often classified as non-differential in the targeted analyses.

Seven studies investigated plasma amino acid profiles (eight cohorts, CRC patients: n = 1045; controls: n = 1920), all employing mass spectrometry (LC–MS n = 5, GC–MS n = 2). Overall, most amino acids were reported as either decreased or non-differential between CRC patients and controls (Fig. 3a). Notably, cysteine, leucine, methionine, tyrosine, and valine were consistently found to be downregulated in CRC patients across all studies. Stratification by analytical approach (targeted vs. untargeted) did not reveal substantial differences in overall findings (Supplementary Fig. 1).

Urine samples were analysed in six studies (six cohorts, CRC patients: n = 696; controls: n = 687), with mass spectrometry being the predominant technique (5/6 studies; 83%), including LC–MS (n = 4) and CE–MS (n = 1). NMR spectroscopy was applied in one study (17%). Most amino acids were reported as either non-differential or differentially altered in only one or two studies (Fig. 3a). Compared to other matrices, urine-based studies revealed more distinct patterns by analytical approach: targeted studies mainly reported no significant differences, while untargeted studies identified various altered amino acids (Supplementary Fig. 1). However, none of the three untargeted studies identified the same amino acids as differential [16–18]. This finding should be interpreted with caution, as selective reporting of only significant metabolites in untargeted studies may have influenced comparability.

Tissue-based analyses, comprising 23 studies (29 cohorts, CRC patients: n = 1101; controls: n = 1076), revealed the most consistent profile across all matrices, with all amino acids identified as upregulated in CRC tissue relative to normal mucosa (Fig. 3a). Only a small number of studies reported downregulated or non-differential levels. Glutamine was the exception, showing an equal number of studies reporting up- and downregulation, and one study reporting no significant difference. Several amino acids, including aspartic acid, cysteine, histidine, isoleucine, lysine, methionine, serine, threonine, and tryptophan, were consistently found to be significantly increased in all studies that assessed them. Similar to the other matrices, mass spectrometry was the predominant analytical technique, used in 16 of 23 studies (70%), including LC–MS (n = 7), GC–MS (n = 7), TOF–SIMS (n = 1), and CE–MS (n = 1). NMR spectroscopy was employed in 8 studies (35%).

Only one study investigated saliva samples using untargeted LC–MS and found decreased levels of arginine, aspartic acid, histidine, methionine, phenylalanine, serine, and tryptophan in 35 CRC patients compared to 36 controls. While some overlap with results from plasma and untargeted serum analyses, the overall pattern remained inconsistent and non-specific. Cysteine showed a relatively distinct trend, being consistently downregulated in urine, serum, and plasma, elevated in tissue, and largely non-differential in faecal samples. However, this observation is based on a limited number of studies per matrix and should be interpreted with caution.

Amino acid profiles in advanced adenoma versus controls

Supplementary Table 5 shows an overview of all findings in the advanced adenoma versus controls comparison. Four studies, comprising five independent cohorts, examined amino acid profiles in faecal (three studies, advanced adenoma patients: n = 154, controls: n = 162) and serum (one study comprising two cohorts, advanced adenoma patients: n = 76, controls: n = 64) samples from individuals with advanced adenoma compared to controls. Overall, most studies did not report significant differences in amino acid profiles, although a few individual amino acids were found to differ significantly (Fig. 3b, Supplementary Table 5). In one faecal cohort, targeted HPLC analysis showed elevated levels of alanine, glutamate, glycine, proline, serine, threonine, and valine in advanced adenoma patients compared to controls [14]. However, these findings were not in line with two untargeted studies, using UPLC-MS, which found no significant differences in the same amino acids [19, 20]. Similarly, in a targeted serum-based study using LC–MS in two independent cohorts, results for aspartic acid and serine were inconsistent: one cohort showed elevated levels in advanced adenoma patients, while the other reported no significant differences [21]. For glycine, opposing trends were observed, with upregulation in one cohort and downregulation in the other.

Amino acid profiles in advanced neoplasia versus controls

Seven studies assessed amino acid profiles in biological samples from individuals with CRC and advanced adenomas, collectively referred to as patients with advanced neoplasia, compared to controls. These included faecal samples (five studies, advanced neoplasia patients: n = 303; controls: n = 438), urine (two studies, advanced neoplasia patients: n = 219; controls: n = 385), and plasma (one study, advanced neoplasia patients: n = 159; controls: n = 229). All outcomes for the advanced neoplasia versus controls comparison are summarised in Supplementary Table 6. Overall, amino acid levels in faecal and plasma samples were predominantly non-differential between groups (Fig. 3c). In contrast, most urinary amino acids were decreased in advanced neoplasia patients, based on a targeted LC–MS approach [22]. However, inconsistent results were found for alanine, proline, and valine when compared to findings from an untargeted NMR-based study [22, 23]. Notably, threonine was found to be downregulated in both urine and plasma within the same study applying targeted LC–MS/MS [22]. Although certain amino acids were consistently reported as non-differential across sample types, the findings did not point to a clear amino acid signature for advanced neoplasia.

Diagnostic potential

Several studies evaluated the diagnostic potential of individual amino acids for detecting CRC in various biological matrices: faeces (n = 3), urine (n = 1), serum (n = 6), plasma (n = 2), and tissue (n = 2). The diagnostic performance of individual amino acids across matrices is detailed in Supplementary Table 9, with most studies reporting area under the curve (AUC) values derived from ROC curve analysis. An overview of these AUCs is illustrated in Fig. 4. AUC values varied widely, ranging from poor to good discriminative ability depending on the matrix and amino acid. The highest values were observed in the faecal analysis by Lin et al., where alanine, glutamate, glutamine, isoleucine, leucine, proline, and valine achieved AUCs between 0.84 and 0.91 for the detection of stage I and II CRC [24]. Elevated AUCs were also described for tissue-based aspartic acid (AUC 0.89), serum glutamine (AUC 0.81), and urinary alanine (AUC 0.81) [11, 25, 26]. While most findings lacked validation, tissue-based aspartic acid was confirmed in an independent test set, though this was based on a limited sample size [25]. Additionally, Kim et al. reported a validated AUC of 0.783 (95% CI 0.714–0.839) for urinary alanine in detecting CRC and advanced adenomas [23]. No single amino acid consistently demonstrated good diagnostic performance (AUC ≥ 0.80) across multiple matrices. In many studies, multivariate diagnostic panels were constructed using combinations of amino acids and other metabolites. As these panels did not consist exclusively of amino acids, they fall outside the scope of this review and are not further discussed.

Fig. 4: Overview of AUC values for amino acids by sample matrix for CRC detection. Forest plot displaying the reported AUC values for each amino acid in the comparison between CRC and controls. Each row represents a unique amino acid and biological matrix, showing the estimated AUC and its corresponding confidence interval, as reported in the referenced study (author and year in coloured y-axis labels). For some studies, no confidence interval was provided and only the AUC is shown. The colour of the data points reflects the matrix type and corresponds to the legend. MEV microbial extracellular vesicles