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Table 4 12 driver genes predicted by EARN50 which are confirmed for metastatic cancers in the HCMDB

From: EARN: an ensemble machine learning algorithm to predict driver genes in metastatic breast cancer

Symbol Prediction score Rank PSMM (%) [54] PSMM (%) [55] NSCGMCH NSCGMBH MCMGM PKGECC PKGEBC
APEX1 0.900511991 5 0.50 1.70 1 #N/A 5 #N/A #N/A
ARID1A 0.895213526 11 2.40 5.10 2 #N/A 24
KDM6B 0.894029187 13 1.40 4.60 1 #N/A 16 #N/A #N/A
TBX3 0.893837209 14 2.80 5.10 1 #N/A 21
KDRa 0.890079401 17 0.90 1.70 7 2 9 #N/A
SERPINE2 0.889205475 19 0.90 0.80 1 #N/A 4 #N/A #N/A
TBL1XR1 0.871240171 27 0.90 0.80 2 #N/A 4
KRAS 0.868267682 30 1.40 1.70 20 #N/A 7
NOS3 0.861560093 31 2.40 2.10 1 #N/A 12 #N/A #N/A
RAPGEF3 0.851947423 42 #N/A 2.50 2 #N/A 6 #N/A #N/A
SELEa 0.847865292 49 0.90 1.30 12 1 5 #N/A #N/A
MMEa 0.847698297 50 0.90 2.50 9 1 9 #N/A #N/A
  1. Also, the rank number, score, and mutation count for these genes are provided in the table. The confirmed genes as the known genes related to any primary cancers or primary breast tumors in OMIM, CGC, and NCG databases have been marked in the last two columns
  2. PSMM, Percentage of samples with one or more mutations based on initial mutation file, NSCGMCH, Number of studies that have cited genes related to different metastatic cancers in the HCMDB, NSCGMBH, Number of studies that have cited genes related to metastatic breast cancer in HCMDB, MCMGM, Mutation counts for mutated genes across 450 metastasis tumor samples based on the initial mutation file, PKGECC, Predicted known genes by EC associated with different cancers that are confirmed in OMIM, CGC, and NCG, PKGEBC, Predicted known genes by EC associated with breast cancer that are confirmed in OMIM, CGC, and NCG
  3. aThese genes have been specifically introduced concerning metastatic breast cancer