Table 4.
List of proteins from prostate, bladder, and kidney cancers included in meta-analysis. Combined statistics for these proteins are also depicted.
| Protein Name |
Cancer Type |
Expression Trend | Combined and Weighted p-Value | Combined and Weighted Fold Change | N_Total | Reference |
|---|---|---|---|---|---|---|
| AMBP | Prostate | Up | 1.35339 × 10−19 | 2.34 | 114 | Fujita et al., 2017 [19]; Davalieva et al., 2015 [18]; Davalieva et al., 2015 [18]; Davalieva et al., 2015 [18]; Davalieva et al., 2015 [18] |
| CALD1 | Prostate | Up | 8.32538 × 10−11 | 3.66 | 12 | Webber et al., 2016 [20]; Webber et al., 2016 [20] |
| CD59 | Prostate | Up | 0.001010766 | 3.91 | 72 | Davalieva et al., 2015 [18]; Davalieva et al., 2015 [18]; Davalieva et al., 2015 [18] |
| FABP5 | Prostate | Up | 0.000586891 | 2.80 | 70 | Fujita et al., 2017 [19]; Davalieva et al., 2015 [37] |
| ITIH4 | Prostate | Up | 4.26138 × 10−6 | 2.69 | 48 | Davalieva et al., 2015 [18]; Davalieva et al., 2015 [18] |
| MARCS | Prostate | Up | 4.4686 × 10−5 | 2.67 | 12 | Webber et al., 2016 [20]; Webber et al., 2016 [20] |
| NME1 | Prostate | Up | 1.2542 × 10−17 | 3.04 | 60 | Davalieva et al., 2015 [37]; Jiang et al., 2013 |
| NPM | Prostate | Up | 0.000242959 | 2.33 | 12 | Webber et al., 2016 [20]; Webber et al., 2016 [20] |
| PTGDS | Prostate | Up | 0.001369911 | 3.38 | 48 | Davalieva et al., 2015 [18]; Davalieva et al., 2015 [18] |
| SCTM1 | Prostate | Up | 4.10108 × 10−5 | 6.38 | 48 | Davalieva et al., 2015 [18]; Davalieva et al., 2015 [18] |
| C3 | Bladder | Up | 0.001339534 | 2.07 | 17 | Nedjadi et al., 2020 [24]; Sathe et al., 2020 [28] |
| EHD4 | Bladder | Up | 0.004667281 | 5.99 | 29 | Smalley et al., 2007 [29]; Lee et al., 2018 [27] |
| LGALS3BP | Bladder | Up | 0 | 1.71 | 93 | Gómez et al., 2021; Smalley et al., 2007 [29] |
| S100A8 | Bladder | Up | 0.000434476 | 2.98 | 99 | Sathe et al., 2020 [28]; Bansal et al., 2014 [25] |
| ALDOA | Kidney | Up | 0 | 2.903563795 | 72 | Song et al., 2017 [30]; Okamura et al., 2008 [34]; WeiBer et al., 2015 [36]; Perroud et al., 2009 [35] |
| ANXA4 | Kidney | Up | 8.87564 × 10−15 | 6.63931328 | 72 | Song et al., 2017 [30]; Okamura et al., 2008 [34]; WeiBer et al., 2015 [36] |
| COL18A1 | Kidney | Down | 6.83113 × 10−8 | 0.2 | 64 | Song et al., 2017 [30]; Okamura et al., 2008 [34]; Perroud et al., 2009 [35] |
| COX6B1 | Kidney | Down | 2.04982 × 10−6 | 0.2 | 56 | Song et al., 2017 [30]; Okamura et al., 2008 [34] |
| CRYAB | Kidney | Up | 5.68212 × 10−5 | 2.765541687 | 84 | Okamura et al., 2008 [34]; WeiBer et al., 2015 [36]; Giribaldi et al., 2013; Giribaldi et al., 2013 [31] |
| FABP1 | Kidney | Down | 3.10267 × 10−5 | 0.1 | 36 | Song et al., 2017 [30]; WeiBer et al., 2015 [36] |
| LDHA | Kidney | Up | 3.56554 × 10−6 | 5.580626486 | 72 | Song et al., 2017 [30]; Okamura et al., 2008 [34]; WeiBer et al., 2015 [36]; Perroud et al., 2009 [35] |
| PCK2 | Kidney | Down | 1.13664 × 10−5 | 0.176347496 | 64 | Song et al., 2017 [30]; Okamura et al., 2008 [34]; WeiBer et al., 2015 [36] |
| PEBP1 | Kidney | Down | 1.56604 × 10−9 | 0.302889369 | 112 | Song et al., 2017 [30]; Okamura et al., 2008 [34]; Perroud et al., 2009 [35]; Giribaldi et al., 2013 [35] |
| PKM | Kidney | Up | 6.44029 × 10−7 | 3.672247556 | 64 | Song et al., 2017 [30]; Okamura et al., 2008 [34]; WeiBer et al., 2015 [36] |