This report serves to describe the mutational landscape and properties of a given individual set, as well as rank genes and genesets according to mutational significance. MutSig v2.0 was used to generate the results found in this report.
Working with individual set: STAD.
Number of patients in set: 133
The input for this pipeline is a set of individuals with the following files associated for each:
1. An annotated .maf file describing the mutations called for the respective individual, and their properties.
2. A .wig file that contains information about the coverage of the sample.
MAF used for this analysis: STAD.final_analysis_set.maf
Significantly mutated genes (q ≤ 0.1): 92
Mutations seen in COSMIC: 342
Significantly mutated genes in COSMIC territory: 22
Genes with clustered mutations (≤ 3 aa apart): 0
Significantly mutated genesets: 13
Significantly mutated genesets: (excluding sig. mutated genes): 0
Read 133 MAFs of type "Broad"
Total number of mutations in input MAFs: 267713
After removing 171098 noncoding mutations: 96615
After collapsing adjacent/redundant mutations: 77270
Number of mutations before filtering: 77270
After removing 396 mutations outside gene set: 76874
After removing 95 mutations outside category set: 76779
After removing 2 "impossible" mutations in
gene-patient-category bins of zero coverage: 76777
Table 1. Get Full Table Table representing breakdown of mutations by type.
| type | count |
|---|---|
| Frame_Shift_Del | 2059 |
| Frame_Shift_Ins | 306 |
| In_Frame_Del | 141 |
| In_Frame_Ins | 18 |
| Missense_Mutation | 49582 |
| Nonsense_Mutation | 2293 |
| Nonstop_Mutation | 52 |
| Silent | 21076 |
| Splice_Site | 1222 |
| Translation_Start_Site | 30 |
| Total | 76779 |
Table 2. Get Full Table A breakdown of mutation rates per category discovered for this individual set.
| category | n | N | rate | rate_per_mb | relative_rate | exp_ns_s_ratio |
|---|---|---|---|---|---|---|
| *CpG->T | 17232 | 213212487 | 0.000081 | 81 | 5.7 | 2.1 |
| *Np(A/C/T)->transit | 16836 | 3086012671 | 5.5e-06 | 5.5 | 0.38 | 2 |
| *ApG->G | 2333 | 597942472 | 3.9e-06 | 3.9 | 0.27 | 2.1 |
| transver | 13197 | 3897167630 | 3.4e-06 | 3.4 | 0.24 | 5 |
| indel+null | 6013 | 3897167630 | 1.5e-06 | 1.5 | 0.11 | NaN |
| double_null | 91 | 3897167630 | 2.3e-08 | 0.023 | 0.0016 | NaN |
| Total | 55702 | 3897167630 | 0.000014 | 14 | 1 | 3.5 |
The x axis represents the samples. The y axis represents the exons, one row per exon, and they are sorted by average coverage across samples. For exons with exactly the same average coverage, they are sorted next by the %GC of the exon. (The secondary sort is especially useful for the zero-coverage exons at the bottom).
Figure 1.
Figure 2. Patients counts and rates file used to generate this plot: STAD.patients.counts_and_rates.txt
Figure 3. Get High-res Image The matrix in the center of the figure represents individual mutations in patient samples, color-coded by type of mutation, for the significantly mutated genes. The rate of synonymous and non-synonymous mutations is displayed at the top of the matrix. The barplot on the left of the matrix shows the number of mutations in each gene. The percentages represent the fraction of tumors with at least one mutation in the specified gene. The barplot to the right of the matrix displays the q-values for the most significantly mutated genes. The purple boxplots below the matrix (only displayed if required columns are present in the provided MAF) represent the distributions of allelic fractions observed in each sample. The plot at the bottom represents the base substitution distribution of individual samples, using the same categories that were used to calculate significance.
Table 3. Get Full Table A Ranked List of Significantly Mutated Genes. Number of significant genes found: 92. Number of genes displayed: 35. Click on a gene name to display its stick figure depicting the distribution of mutations and mutation types across the chosen gene (this feature may not be available for all significant genes).
| rank | gene | description | N | n | npat | nsite | nsil | n1 | n2 | n3 | n4 | n5 | n6 | p_classic | p_ns_s | p_ks | p_cons | p_joint | p | q |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 1 | TP53 | tumor protein p53 | 165051 | 67 | 62 | 48 | 2 | 21 | 13 | 2 | 10 | 20 | 1 | <1.00e-15 | 2.1e-06 | 2e-07 | 2e-07 | 0 | <1.00e-15 | <1.64e-12 |
| 2 | ACVR2A | activin A receptor, type IIA | 210899 | 18 | 17 | 5 | 0 | 0 | 3 | 0 | 1 | 14 | 0 | <1.00e-15 | 0.28 | 2e-07 | 0.0024 | 0 | <1.00e-15 | <1.64e-12 |
| 3 | CBWD1 | COBW domain containing 1 | 131067 | 18 | 17 | 3 | 0 | 0 | 2 | 0 | 0 | 16 | 0 | <1.00e-15 | 0.037 | 2e-07 | 2.4e-06 | 0 | <1.00e-15 | <1.64e-12 |
| 4 | KRAS | v-Ki-ras2 Kirsten rat sarcoma viral oncogene homolog | 93127 | 17 | 17 | 8 | 0 | 0 | 12 | 0 | 5 | 0 | 0 | <1.00e-15 | 0.0055 | 2e-06 | 0.00041 | 0 | <1.00e-15 | <1.64e-12 |
| 5 | RPL22 | ribosomal protein L22 | 50726 | 10 | 10 | 1 | 0 | 0 | 0 | 0 | 0 | 10 | 0 | 1.29e-12 | 1 | 2e-07 | 0.031 | 0 | <1.00e-15 | <1.64e-12 |
| 6 | PRRT2 | proline-rich transmembrane protein 2 | 134137 | 5 | 5 | 2 | 1 | 0 | 0 | 0 | 1 | 4 | 0 | 0.0021 | 0.93 | 2e-07 | 0.21 | 0 | <1.00e-15 | <1.64e-12 |
| 7 | SMAP1 | stromal membrane-associated GTPase-activating protein 1 | 178580 | 5 | 5 | 1 | 2 | 0 | 0 | 0 | 0 | 5 | 0 | 0.0088 | 1 | 2e-07 | 0.3 | 0 | <1.00e-15 | <1.64e-12 |
| 8 | DNAJC15 | DnaJ (Hsp40) homolog, subfamily C, member 15 | 58957 | 3 | 3 | 3 | 0 | 1 | 0 | 0 | 1 | 1 | 0 | 0.0052 | 0.4 | 0.045 | 0.014 | 0 | <1.00e-15 | <1.64e-12 |
| 9 | EFNA2 | ephrin-A2 | 47344 | 2 | 2 | 2 | 0 | 1 | 0 | 0 | 0 | 1 | 0 | 0.074 | 0.38 | 0.025 | 0.7 | 0 | <1.00e-15 | <1.64e-12 |
| 10 | NSF | N-ethylmaleimide-sensitive factor | 163988 | 2 | 2 | 2 | 3 | 0 | 0 | 1 | 0 | 1 | 0 | 0.62 | 0.99 | 0.00034 | 0.75 | 0 | <1.00e-15 | <1.64e-12 |
| 11 | HPGDS | 82460 | 2 | 1 | 2 | 0 | 0 | 1 | 0 | 0 | 1 | 0 | 0.39 | 0.5 | 0.0031 | 0.88 | 0 | <1.00e-15 | <1.64e-12 | |
| 12 | TRIM48 | tripartite motif-containing 48 | 84892 | 14 | 14 | 3 | 0 | 0 | 13 | 0 | 1 | 0 | 0 | 2.18e-12 | 0.0032 | 2e-07 | 0.91 | 0.000022 | 1.89e-15 | 2.83e-12 |
| 13 | PGM5 | phosphoglucomutase 5 | 187631 | 21 | 18 | 7 | 0 | 5 | 14 | 0 | 0 | 2 | 0 | 8.06e-11 | 0.00034 | 2e-07 | 1 | 0.000018 | 5.16e-14 | 7.15e-11 |
| 14 | ARID1A | AT rich interactive domain 1A (SWI-like) | 773196 | 28 | 26 | 27 | 2 | 4 | 1 | 0 | 5 | 15 | 3 | 2.94e-14 | 0.064 | 0.78 | 0.23 | 0.46 | 4.41e-13 | 5.67e-10 |
| 15 | ZNF804B | zinc finger protein 804B | 540495 | 23 | 21 | 22 | 1 | 0 | 8 | 0 | 12 | 3 | 0 | 3.99e-12 | 0.019 | 0.26 | 0.71 | 0.45 | 5.00e-11 | 5.99e-08 |
| 16 | FGF22 | fibroblast growth factor 22 | 22304 | 4 | 4 | 1 | 1 | 0 | 0 | 0 | 0 | 4 | 0 | 0.000015 | 1 | 4e-07 | 1 | 4e-07 | 1.57e-10 | 1.75e-07 |
| 17 | PIK3CA | phosphoinositide-3-kinase, catalytic, alpha polypeptide | 437042 | 33 | 25 | 19 | 3 | 5 | 20 | 3 | 4 | 1 | 0 | 7.00e-08 | 0.0045 | 0.0018 | 0.0089 | 0.000088 | 1.65e-10 | 1.75e-07 |
| 18 | RHOA | ras homolog gene family, member A | 79534 | 8 | 7 | 4 | 0 | 0 | 5 | 0 | 3 | 0 | 0 | 1.01e-07 | 0.089 | 9.2e-06 | 0.16 | 0.000078 | 2.09e-10 | 2.09e-07 |
| 19 | INO80E | 53262 | 9 | 9 | 4 | 0 | 1 | 0 | 0 | 1 | 6 | 1 | 1.48e-09 | 0.51 | 0.45 | 0.002 | 0.0082 | 3.19e-10 | 3.02e-07 | |
| 20 | OR8H3 | olfactory receptor, family 8, subfamily H, member 3 | 125419 | 10 | 10 | 8 | 1 | 0 | 4 | 3 | 3 | 0 | 0 | 2.23e-08 | 0.1 | 0.26 | 0.011 | 0.017 | 8.61e-09 | 7.75e-06 |
| 21 | SFRS12IP1 | SFRS12-interacting protein 1 | 61056 | 5 | 5 | 1 | 0 | 0 | 0 | 0 | 0 | 5 | 0 | 0.000079 | 1 | 2e-07 | 0.46 | 0.000017 | 2.93e-08 | 0.000025 |
| 22 | RNF43 | ring finger protein 43 | 289155 | 16 | 15 | 9 | 2 | 1 | 4 | 0 | 0 | 11 | 0 | 6.56e-07 | 0.42 | 0.0049 | 0.16 | 0.0075 | 9.92e-08 | 0.000081 |
| 23 | PCDH15 | protocadherin 15 | 988063 | 25 | 23 | 25 | 3 | 2 | 5 | 5 | 8 | 5 | 0 | 1.97e-08 | 0.02 | 0.18 | 0.98 | 0.31 | 1.22e-07 | 0.000095 |
| 24 | CDH1 | cadherin 1, type 1, E-cadherin (epithelial) | 338076 | 14 | 13 | 14 | 4 | 1 | 5 | 1 | 5 | 2 | 0 | 0.000031 | 0.39 | 0.013 | 0.0025 | 0.00036 | 2.15e-07 | 0.00016 |
| 25 | TUSC3 | tumor suppressor candidate 3 | 142522 | 11 | 11 | 10 | 0 | 5 | 1 | 0 | 5 | 0 | 0 | 1.46e-07 | 0.078 | 0.081 | 0.33 | 0.11 | 3.13e-07 | 0.00023 |
| 26 | SMAD4 | SMAD family member 4 | 226261 | 9 | 8 | 8 | 1 | 3 | 1 | 0 | 2 | 3 | 0 | 2.15e-06 | 0.32 | 0.013 | 0.073 | 0.0093 | 3.73e-07 | 0.00026 |
| 27 | IAPP | islet amyloid polypeptide | 36974 | 4 | 4 | 3 | 0 | 0 | 0 | 0 | 4 | 0 | 0 | 0.000045 | 0.47 | 0.00029 | 0.98 | 0.00073 | 6.06e-07 | 0.00040 |
| 28 | PHF2 | PHD finger protein 2 | 350230 | 14 | 13 | 5 | 4 | 2 | 1 | 0 | 1 | 10 | 0 | 0.00034 | 0.88 | 4e-05 | 0.45 | 0.00012 | 7.20e-07 | 0.00046 |
| 29 | SPRYD5 | SPRY domain containing 5 | 121763 | 8 | 8 | 6 | 0 | 0 | 0 | 1 | 2 | 5 | 0 | 5.48e-08 | 0.45 | 0.77 | 1 | 1 | 9.71e-07 | 0.00060 |
| 30 | IRF2 | interferon regulatory factor 2 | 143858 | 10 | 8 | 10 | 1 | 4 | 0 | 0 | 4 | 1 | 1 | 0.00020 | 0.2 | 0.004 | 0.018 | 0.00051 | 1.77e-06 | 0.0011 |
| 31 | C17orf63 | chromosome 17 open reading frame 63 | 9845 | 4 | 4 | 4 | 0 | 2 | 0 | 0 | 1 | 1 | 0 | 2.02e-06 | 0.16 | NaN | NaN | NaN | 2.02e-06 | 0.0012 |
| 32 | CCDC43 | coiled-coil domain containing 43 | 84224 | 4 | 4 | 2 | 0 | 0 | 0 | 0 | 1 | 3 | 0 | 0.0053 | 0.85 | 3.4e-06 | 0.59 | 0.000026 | 2.29e-06 | 0.0013 |
| 33 | HLA-A | major histocompatibility complex, class I, A | 144803 | 10 | 9 | 10 | 1 | 0 | 2 | 3 | 3 | 2 | 0 | 9.89e-06 | 0.23 | 0.13 | 0.0074 | 0.015 | 2.54e-06 | 0.0014 |
| 34 | PTH2 | parathyroid hormone 2 | 26182 | 3 | 3 | 1 | 0 | 0 | 0 | 0 | 3 | 0 | 0 | 0.00029 | 0.43 | 0.000038 | 0.11 | 0.00076 | 3.57e-06 | 0.0019 |
| 35 | TLR4 | toll-like receptor 4 | 336693 | 13 | 13 | 11 | 2 | 0 | 2 | 3 | 8 | 0 | 0 | 3.56e-06 | 0.32 | 0.031 | 0.92 | 0.065 | 3.79e-06 | 0.0019 |
Figure S1. This figure depicts the distribution of mutations and mutation types across the TP53 significant gene.
Figure S2. This figure depicts the distribution of mutations and mutation types across the ACVR2A significant gene.
Figure S3. This figure depicts the distribution of mutations and mutation types across the KRAS significant gene.
Figure S4. This figure depicts the distribution of mutations and mutation types across the RPL22 significant gene.
Figure S5. This figure depicts the distribution of mutations and mutation types across the PRRT2 significant gene.
Figure S6. This figure depicts the distribution of mutations and mutation types across the SMAP1 significant gene.
Figure S7. This figure depicts the distribution of mutations and mutation types across the DNAJC15 significant gene.
Figure S8. This figure depicts the distribution of mutations and mutation types across the EFNA2 significant gene.
Figure S9. This figure depicts the distribution of mutations and mutation types across the NSF significant gene.
Figure S10. This figure depicts the distribution of mutations and mutation types across the HPGDS significant gene.
Figure S11. This figure depicts the distribution of mutations and mutation types across the TRIM48 significant gene.
Figure S12. This figure depicts the distribution of mutations and mutation types across the PGM5 significant gene.
Figure S13. This figure depicts the distribution of mutations and mutation types across the ARID1A significant gene.
Figure S14. This figure depicts the distribution of mutations and mutation types across the ZNF804B significant gene.
Figure S15. This figure depicts the distribution of mutations and mutation types across the FGF22 significant gene.
Figure S16. This figure depicts the distribution of mutations and mutation types across the PIK3CA significant gene.
Figure S17. This figure depicts the distribution of mutations and mutation types across the RHOA significant gene.
Figure S18. This figure depicts the distribution of mutations and mutation types across the INO80E significant gene.
Figure S19. This figure depicts the distribution of mutations and mutation types across the OR8H3 significant gene.
Figure S20. This figure depicts the distribution of mutations and mutation types across the RNF43 significant gene.
Figure S21. This figure depicts the distribution of mutations and mutation types across the PCDH15 significant gene.
Figure S22. This figure depicts the distribution of mutations and mutation types across the CDH1 significant gene.
Figure S23. This figure depicts the distribution of mutations and mutation types across the TUSC3 significant gene.
Figure S24. This figure depicts the distribution of mutations and mutation types across the SMAD4 significant gene.
Figure S25. This figure depicts the distribution of mutations and mutation types across the PHF2 significant gene.
Figure S26. This figure depicts the distribution of mutations and mutation types across the SPRYD5 significant gene.
Figure S27. This figure depicts the distribution of mutations and mutation types across the IRF2 significant gene.
Figure S28. This figure depicts the distribution of mutations and mutation types across the C17orf63 significant gene.
Figure S29. This figure depicts the distribution of mutations and mutation types across the CCDC43 significant gene.
Figure S30. This figure depicts the distribution of mutations and mutation types across the HLA-A significant gene.
Note:
N - number of sequenced bases in this gene across the individual set.
n - number of (nonsilent) mutations in this gene across the individual set.
npat - number of patients (individuals) with at least one nonsilent mutation.
nsite - number of unique sites having a non-silent mutation.
nsil - number of silent mutations in this gene across the individual set.
n1 - number of nonsilent mutations of type: *CpG->T .
n2 - number of nonsilent mutations of type: *Np(A/C/T)->transit .
n3 - number of nonsilent mutations of type: *ApG->G .
n4 - number of nonsilent mutations of type: transver .
n5 - number of nonsilent mutations of type: indel+null .
null - mutation category that includes nonsense, frameshift, splice-site mutations
p_classic = p-value for the observed amount of nonsilent mutations being elevated in this gene
p_ns_s = p-value for the observed nonsilent/silent ratio being elevated in this gene
p = p-value (overall)
q = q-value, False Discovery Rate (Benjamini-Hochberg procedure)
In this analysis, COSMIC is used as a filter to increase power by restricting the territory of each gene. Cosmic version: v48.
Table 4. Get Full Table Significantly mutated genes (COSMIC territory only). To access the database please go to: COSMIC. Number of significant genes found: 22. Number of genes displayed: 10
| rank | gene | description | n | cos | n_cos | N_cos | cos_ev | p | q |
|---|---|---|---|---|---|---|---|---|---|
| 1 | ACVR2A | activin A receptor, type IIA | 18 | 3 | 14 | 399 | 14 | 7.3e-15 | 3.3e-11 |
| 2 | KRAS | v-Ki-ras2 Kirsten rat sarcoma viral oncogene homolog | 17 | 51 | 15 | 6783 | 100690 | 1.1e-13 | 2.5e-10 |
| 3 | PIK3CA | phosphoinositide-3-kinase, catalytic, alpha polypeptide | 33 | 184 | 30 | 24472 | 10503 | 3.2e-13 | 4.7e-10 |
| 4 | TP53 | tumor protein p53 | 67 | 308 | 63 | 40964 | 21281 | 4.2e-13 | 4.7e-10 |
| 5 | SMAD4 | SMAD family member 4 | 9 | 159 | 8 | 21147 | 25 | 1.3e-09 | 1.2e-06 |
| 6 | CDH1 | cadherin 1, type 1, E-cadherin (epithelial) | 14 | 184 | 8 | 24472 | 32 | 4.1e-09 | 3.1e-06 |
| 7 | FBXW7 | F-box and WD repeat domain containing 7 | 11 | 91 | 6 | 12103 | 279 | 3.2e-08 | 0.000021 |
| 8 | ERBB3 | v-erb-b2 erythroblastic leukemia viral oncogene homolog 3 (avian) | 21 | 6 | 3 | 798 | 3 | 2.4e-07 | 0.00014 |
| 9 | PKHD1 | polycystic kidney and hepatic disease 1 (autosomal recessive) | 20 | 8 | 3 | 1064 | 3 | 5.8e-07 | 0.00029 |
| 10 | SMAD2 | SMAD family member 2 | 8 | 10 | 3 | 1330 | 9 | 1.1e-06 | 0.00051 |
Note:
n - number of (nonsilent) mutations in this gene across the individual set.
cos = number of unique mutated sites in this gene in COSMIC
n_cos = overlap between n and cos.
N_cos = number of individuals times cos.
cos_ev = total evidence: number of reports in COSMIC for mutations seen in this gene.
p = p-value for seeing the observed amount of overlap in this gene)
q = q-value, False Discovery Rate (Benjamini-Hochberg procedure)
There were no clustered mutations discovered.
Table 5. Get Full Table A Ranked List of Significantly Mutated Genesets. (Source: MSigDB GSEA Cannonical Pathway Set).Number of significant genesets found: 13. Number of genesets displayed: 10
| rank | geneset | description | genes | N_genes | mut_tally | N | n | npat | nsite | nsil | n1 | n2 | n3 | n4 | n5 | n6 | p_ns_s | p | q |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 1 | ARFPATHWAY | Cyclin-dependent kinase inhibitor 2A is a tumor suppressor that induces G1 arrest and can activate the p53 pathway, leading to G2/M arrest. | ABL1, CDKN2A, E2F1, MDM2, MYC, PIK3CA, PIK3R1, POLR1A, POLR1B, POLR1C, POLR1D, RAC1, RB1, TBX2, TP53, TWIST1 | 16 | ABL1(2), CDKN2A(4), MDM2(3), PIK3CA(33), PIK3R1(7), POLR1A(8), POLR1B(2), POLR1C(2), POLR1D(1), RB1(8), TBX2(4), TP53(67), TWIST1(1) | 4003294 | 142 | 87 | 108 | 24 | 36 | 48 | 6 | 21 | 30 | 1 | 0.000054 | <1.00e-15 | <8.80e-14 |
| 2 | P53HYPOXIAPATHWAY | Hypoxia induces p53 accumulation and consequent apoptosis with p53-mediated cell cycle arrest, which is present under conditions of DNA damage. | ABCB1, AKT1, ATM, BAX, CDKN1A, CPB2, CSNK1A1, CSNK1D, FHL2, GADD45A, HIC1, HIF1A, HSPA1A, HSPCA, IGFBP3, MAPK8, MDM2, NFKBIB, NQO1, TP53 | 19 | ABCB1(10), AKT1(2), ATM(17), CDKN1A(1), CPB2(4), CSNK1D(2), FHL2(2), HIC1(1), HIF1A(2), HSPA1A(1), IGFBP3(4), MAPK8(4), MDM2(3), NFKBIB(4), NQO1(3), TP53(67) | 4118242 | 127 | 84 | 107 | 21 | 40 | 33 | 4 | 19 | 29 | 2 | 0.0002 | <1.00e-15 | <8.80e-14 |
| 3 | RBPATHWAY | The ATM protein kinase recognizes DNA damage and blocks cell cycle progression by phosphorylating chk1 and p53, which normally inhibits Rb to allow G1/S transitions. | ATM, CDC2, CDC25A, CDC25B, CDC25C, CDK2, CDK4, CHEK1, MYT1, RB1, TP53, WEE1, YWHAH | 12 | ATM(17), CDC25A(2), CDC25B(4), CDC25C(3), CDK2(2), CHEK1(2), MYT1(12), RB1(8), TP53(67), WEE1(1), YWHAH(1) | 3508527 | 119 | 78 | 98 | 12 | 37 | 31 | 5 | 16 | 28 | 2 | 4.4e-06 | <1.00e-15 | <8.80e-14 |
| 4 | PLK3PATHWAY | Active Plk3 phosphorylates CDC25c, blocking the G2/M transition, and phosphorylates p53 to induce apoptosis. | ATM, ATR, CDC25C, CHEK1, CHEK2, CNK, TP53, YWHAH | 7 | ATM(17), ATR(5), CDC25C(3), CHEK1(2), CHEK2(5), TP53(67), YWHAH(1) | 3188811 | 100 | 77 | 80 | 11 | 32 | 24 | 4 | 13 | 25 | 2 | 0.00047 | <1.00e-15 | <8.80e-14 |
| 5 | SA_G1_AND_S_PHASES | Cdk2, 4, and 6 bind cyclin D in G1, while cdk2/cyclin E promotes the G1/S transition. | ARF1, ARF3, CCND1, CDK2, CDK4, CDKN1A, CDKN1B, CDKN2A, CFL1, E2F1, E2F2, MDM2, NXT1, PRB1, TP53 | 15 | ARF1(2), CCND1(1), CDK2(2), CDKN1A(1), CDKN2A(4), CFL1(1), E2F2(2), MDM2(3), NXT1(2), PRB1(2), TP53(67) | 1604627 | 87 | 72 | 68 | 11 | 27 | 21 | 3 | 12 | 23 | 1 | 0.00016 | <1.00e-15 | <8.80e-14 |
| 6 | RNAPATHWAY | dsRNA-activated protein kinase phosphorylates elF2a, which generally inhibits translation, and activates NF-kB to provoke inflammation. | CHUK, DNAJC3, EIF2S1, EIF2S2, MAP3K14, NFKB1, NFKBIA, PRKR, RELA, TP53 | 9 | DNAJC3(1), EIF2S1(1), EIF2S2(2), MAP3K14(3), NFKB1(5), RELA(2), TP53(67) | 1951817 | 81 | 67 | 62 | 7 | 24 | 16 | 2 | 16 | 22 | 1 | 0.00014 | <1.00e-15 | <8.80e-14 |
| 7 | TERTPATHWAY | hTERC, the RNA subunit of telomerase, and hTERT, the catalytic protein subunit, are required for telomerase activity and are overexpressed in many cancers. | HDAC1, MAX, MYC, SP1, SP3, TP53, WT1, ZNF42 | 7 | HDAC1(2), MAX(1), SP1(3), SP3(3), TP53(67), WT1(1) | 1390783 | 77 | 67 | 58 | 9 | 24 | 17 | 2 | 11 | 22 | 1 | 0.000094 | <1.00e-15 | <8.80e-14 |
| 8 | TIDPATHWAY | On ligand binding, interferon gamma receptors stimulate JAK2 kinase to phosphorylate STAT transcription factors, which promote expression of interferon responsive genes. | DNAJA3, HSPA1A, IFNG, IFNGR1, IFNGR2, IKBKB, JAK2, LIN7A, NFKB1, NFKBIA, RB1, RELA, TIP-1, TNF, TNFRSF1A, TNFRSF1B, TP53, USH1C, WT1 | 18 | DNAJA3(2), HSPA1A(1), IFNG(2), IFNGR1(2), IFNGR2(1), IKBKB(3), JAK2(8), LIN7A(6), NFKB1(5), RB1(8), RELA(2), TNF(2), TNFRSF1A(3), TNFRSF1B(1), TP53(67), USH1C(1), WT1(1) | 3602378 | 115 | 75 | 94 | 18 | 30 | 27 | 3 | 24 | 30 | 1 | 0.00043 | 1.22e-15 | 9.40e-14 |
| 9 | ATMPATHWAY | The tumor-suppressing protein kinase ATM responds to radiation-induced DNA damage by blocking cell-cycle progression and activating DNA repair. | ABL1, ATM, BRCA1, CDKN1A, CHEK1, CHEK2, GADD45A, JUN, MAPK8, MDM2, MRE11A, NBS1, NFKB1, NFKBIA, RAD50, RAD51, RBBP8, RELA, TP53, TP73 | 19 | ABL1(2), ATM(17), BRCA1(9), CDKN1A(1), CHEK1(2), CHEK2(5), JUN(2), MAPK8(4), MDM2(3), MRE11A(2), NFKB1(5), RAD50(6), RAD51(1), RBBP8(4), RELA(2), TP53(67), TP73(5) | 5915081 | 137 | 83 | 117 | 21 | 36 | 36 | 5 | 26 | 32 | 2 | 0.0004 | 2.11e-15 | 1.44e-13 |
| 10 | CHEMICALPATHWAY | DNA damage promotes Bid cleavage, which stimulates mitochondrial cytochrome c release and consequent caspase activation, resulting in apoptosis. | ADPRT, AKT1, APAF1, ATM, BAD, BAX, BCL2, BCL2L1, BID, CASP3, CASP6, CASP7, CASP9, CYCS, EIF2S1, PRKCA, PRKCB1, PTK2, PXN, STAT1, TLN1, TP53 | 20 | AKT1(2), APAF1(2), ATM(17), BAD(1), BCL2(1), BID(1), CASP3(1), CASP6(1), CASP7(2), CASP9(1), CYCS(1), EIF2S1(1), PTK2(7), PXN(2), STAT1(6), TLN1(13), TP53(67) | 5433042 | 126 | 78 | 106 | 18 | 43 | 32 | 7 | 16 | 26 | 2 | 0.000039 | 3.95e-13 | 2.43e-11 |
Table 6. Get Full Table A Ranked List of Significantly Mutated Genesets (Excluding Significantly Mutated Genes). Number of significant genesets found: 0. Number of genesets displayed: 10
| rank | geneset | description | genes | N_genes | mut_tally | N | n | npat | nsite | nsil | n1 | n2 | n3 | n4 | n5 | n6 | p_ns_s | p | q |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 1 | HSA00472_D_ARGININE_AND_D_ORNITHINE_METABOLISM | Genes involved in D-arginine and D-ornithine metabolism | DAO | 1 | DAO(5) | 143247 | 5 | 5 | 5 | 1 | 1 | 0 | 1 | 1 | 2 | 0 | 0.55 | 0.0039 | 1 |
| 2 | ERBB4PATHWAY | ErbB4 (aka HER4) is a receptor tyrosine kinase that binds neuregulins as well as members of the EGF family, which also target EGF receptors. | ADAM17, ERBB4, NRG2, NRG3, PRKCA, PRKCB1, PSEN1 | 6 | ADAM17(3), ERBB4(18), NRG2(5), NRG3(9), PSEN1(1) | 1780945 | 36 | 27 | 35 | 6 | 8 | 13 | 4 | 7 | 4 | 0 | 0.03 | 0.1 | 1 |
| 3 | TCRMOLECULE | T Cell Receptor and CD3 Complex | CD3D, CD3E, CD3G, CD3Z, TRA@, TRB@ | 3 | CD3E(3), CD3G(2) | 225536 | 5 | 5 | 4 | 1 | 0 | 2 | 1 | 0 | 2 | 0 | 0.68 | 0.11 | 1 |
| 4 | SLRPPATHWAY | Small leucine-rich proteoglycans (SLRPs) interact with and reorganize collagen fibers in the extracellular matrix. | BGN, DCN, DSPG3, FMOD, KERA, LUM | 5 | BGN(2), DCN(2), FMOD(9), KERA(1), LUM(3) | 721456 | 17 | 15 | 17 | 4 | 8 | 3 | 0 | 5 | 1 | 0 | 0.29 | 0.13 | 1 |
| 5 | GABAPATHWAY | Gamma-aminobutyric acid (GABA) is an inhibitory neurotransmitter whose receptor is regulated by Plic-1, gephyrin, and GABARAP, which promote receptor clustering. | DNM1, GABARAP, GABRA1, GABRA2, GABRA3, GABRA4, GABRA5, GABRA6, GPHN, NSF, SRC, UBQLN1 | 11 | DNM1(5), GABRA1(5), GABRA2(5), GABRA3(5), GABRA4(4), GABRA5(5), GABRA6(5), GPHN(7), UBQLN1(4) | 2211584 | 45 | 26 | 45 | 9 | 11 | 10 | 6 | 13 | 5 | 0 | 0.058 | 0.18 | 1 |
| 6 | 1_AND_2_METHYLNAPHTHALENE_DEGRADATION | ADH1A, ADH1A, ADH1B, ADH1C, ADH1B, ADH1C, ADH4, ADH6, ADH7, ADHFE1 | 7 | ADH1A(4), ADH1B(1), ADH1C(3), ADH4(2), ADH6(4), ADH7(2), ADHFE1(6) | 1120150 | 22 | 17 | 21 | 5 | 2 | 9 | 0 | 6 | 5 | 0 | 0.26 | 0.19 | 1 | |
| 7 | FLUMAZENILPATHWAY | Flumazenil is a benzodiazepine receptor antagonist that may induce protective preconditioning in ischemic cardiomyocytes. | GABRA1, GABRA2, GABRA3, GABRA4, GABRA5, GABRA6, GPX1, PRKCE, SOD1 | 9 | GABRA1(5), GABRA2(5), GABRA3(5), GABRA4(4), GABRA5(5), GABRA6(5), GPX1(1), PRKCE(6) | 1565795 | 36 | 24 | 36 | 9 | 13 | 7 | 5 | 10 | 1 | 0 | 0.13 | 0.23 | 1 |
| 8 | EOSINOPHILSPATHWAY | Recruitment of eosinophils in the inflammatory response observed in asthma occurs via the chemoattractant eotaxin binding to the CCR3 receptor. | CCL11, CCL5, CCR3, CSF2, HLA-DRA, HLA-DRB1, IL3, IL5 | 8 | CCL11(1), CCL5(1), CCR3(4), HLA-DRA(3), HLA-DRB1(1), IL3(1) | 602660 | 11 | 10 | 11 | 3 | 4 | 4 | 0 | 2 | 1 | 0 | 0.35 | 0.27 | 1 |
| 9 | TOB1PATHWAY | TGF-beta signaling activates SMADs, which interact with intracellular Tob to maintain unstimulated T cells by repressing IL-2 expression. | CD28, CD3D, CD3E, CD3G, CD3Z, IFNG, IL2, IL2RA, IL4, MADH3, MADH4, TGFB1, TGFB2, TGFB3, TGFBR1, TGFBR2, TGFBR3, TOB1, TOB2, TRA@, TRB@ | 16 | CD3E(3), CD3G(2), IFNG(2), IL2(1), IL2RA(1), TGFB1(3), TGFB2(6), TGFB3(4), TGFBR1(2), TGFBR2(6), TGFBR3(2), TOB1(1), TOB2(5) | 2099747 | 38 | 26 | 37 | 9 | 6 | 15 | 3 | 10 | 4 | 0 | 0.21 | 0.3 | 1 |
| 10 | HSA00641_3_CHLOROACRYLIC_ACID_DEGRADATION | Genes involved in 3-chloroacrylic acid degradation | ADH1A, ADH1B, ADH1C, ADH4, ADH5, ADH6, ADH7, ADHFE1, ALDH1A3, ALDH1B1, ALDH2, ALDH3A1, ALDH3A2, ALDH7A1, ALDH9A1 | 15 | ADH1A(4), ADH1B(1), ADH1C(3), ADH4(2), ADH5(1), ADH6(4), ADH7(2), ADHFE1(6), ALDH1A3(6), ALDH1B1(3), ALDH2(1), ALDH3A1(5), ALDH3A2(5), ALDH9A1(4) | 2628366 | 47 | 29 | 46 | 9 | 7 | 15 | 0 | 16 | 9 | 0 | 0.047 | 0.33 | 1 |
In brief, we tabulate the number of mutations and the number of covered bases for each gene. The counts are broken down by mutation context category: four context categories that are discovered by MutSig, and one for indel and 'null' mutations, which include indels, nonsense mutations, splice-site mutations, and non-stop (read-through) mutations. For each gene, we calculate the probability of seeing the observed constellation of mutations, i.e. the product P1 x P2 x ... x Pm, or a more extreme one, given the background mutation rates calculated across the dataset. [1]
This is an experimental feature. The full results of the analysis summarized in this report can be downloaded from the TCGA Data Coordination Center.