| Literature DB >> 30479693 |
Elena Fountzilas1, Vassiliki Kotoula2,3, Ioannis Tikas3, Kyriaki Manousou4, Kyriaki Papadopoulou3, Christos Poulios2, Vasilios Karavasilis5, Ioannis Efstratiou6, Dimitrios Pectasides7, Kleo Papaparaskeva8, Ioannis Varthalitis9, Christos Christodoulou10, George Papatsibas11, Sofia Chrisafi3, Georgios K Glantzounis12, Amanda Psyrri13, Gerasimos Aravantinos14, Georgia-Angeliki Koliou4, George K Koukoulis15, George E Pentheroudakis16, George Fountzilas3,17.
Abstract
BACKGROUND: We explored the clinical significance of tumor genotypes and immunophenotypes in non-metastatic colorectal cancer (CRC).Entities:
Keywords: ARID1A; BRCA1; CD8; MMR; targeted NGS
Year: 2018 PMID: 30479693 PMCID: PMC6235022 DOI: 10.18632/oncotarget.26256
Source DB: PubMed Journal: Oncotarget ISSN: 1949-2553
Clinicopathological characteristics in the entire cohort and by tumor location (right colon, left colon, rectum)
| Parameter | Entire cohort (n=412) | Right colon (n=139) | Left colon (n=171) | Rectum (n=102) | p-value |
|---|---|---|---|---|---|
| 0.15 | |||||
| Mean +/− SD | 63.1 +/− 10.7 | 63.5 +/− 10.9 | 63.8 +/− 10.5 | 61.5 +/− 10.7 | |
| Median (IQR) | 65.3 (56.5, 71.6) | 64.9 (56.1, 72.3) | 66.3 (57.1, 72.0) | 63.0 (53.4, 70.1) | |
| Min-Max | 28-81 | 28-80 | 28-81 | 28-79 | |
| 0.953 | |||||
| Female | 183 (44.4%) | 62 (44.6%) | 77 (45.0%) | 44 (43.1%) | |
| Male | 229 (55.6%) | 77 (55.4%) | 94 (55.0%) | 58 (56.9%) | |
| N/A | |||||
| Ascending | 62 (15.1%) | 62 (44.9%) | 0 | 0 | |
| Cecum | 48 (11.7%) | 48 (34.8%) | 0 | 0 | |
| Cecum (multifocal) | 2 (0.5%) | 2 (1.4%) | 0 | 0 | |
| Descending | 16 (3.9%) | 0 | 16 (9.4%) | 0 | |
| Hepatic flexure | 10 (2.4%) | 10 (7.2%) | 0 | 0 | |
| Rectosigmoid | 8 (1.9%) | 0 | 8 (4.7%) | 0 | |
| Rectum | 102 (24.9%) | 0 | 0 | 102 (100.0%) | |
| Sigmoid | 138 (33.7%) | 0 | 138 (81.2%) | 0 | |
| Splenic flexure | 8 (2%) | 0 | 8 (4.7%) | 0 | |
| Transverse | 16 (3.9%) | 16 (11.6%) | 0 (0%) | 0 | |
| Missing | 2 | ||||
| No | 375 (96.4%) | 129 (98.5%) | 151 (93.2%) | 95 (99.0%) | |
| Yes | 14 (3.6%) | 2 (1.5%) | 11 (6.8%) | 1 (1.0%) | |
| Missing | 23 | ||||
| No | 345 (88.5%) | 118 (90.1%) | 135 (83.3%) | 92 (94.8%) | |
| Yes | 45 (11.5%) | 13 (9.9%) | 27 (16.7%) | 5 (5.2%) | |
| Missing | 22 | ||||
| N/A | |||||
| T1 | 4 (1.0%) | 0 | 2 (1.2%) | 2 (2.0%) | |
| T2 | 35 (8.5%) | 8 (5.8%) | 12 (7.1%) | 15 (15.0%) | |
| T3 | 329 (79.9%) | 117 (84.2%) | 136 (80.0%) | 76 (76.0%) | |
| T4 | 41 (10.0%) | 14 (10.1%) | 20 (11.8%) | 7 (7.0%) | |
| Missing | 3 | ||||
| 0.542 | |||||
| N0 | 153 (37.5%) | 56 (40.3%) | 60 (35.7%) | 37 (36.6%) | |
| N1 | 176 (43.1%) | 56 (40.3%) | 71 (42.3%) | 49 (48.5%) | |
| N2 | 79 (19.4%) | 27 (19.4%) | 37 (22.0%) | 15 (14.9%) | |
| Missing | 4 | ||||
| N/A | |||||
| I | 15 (3.7%) | 6 (4.3%) | 6 (3.5%) | 3 (3.0%) | |
| IIA | 122 (29.7%) | 43 (30.9%) | 46 (27.1%) | 33 (32.7%) | |
| IIB | 15 (3.7%) | 6 (4.3%) | 8 (4.7%) | 1 (1.0%) | |
| IIIA | 27 (6.6%) | 6 (4.3%) | 10 (5.9%) | 11 (10.9%) | |
| IIIB | 153 (37.3%) | 52 (37.4%) | 63 (37.1%) | 38 (37.6%) | |
| IIIC | 78 (19.0%) | 26 (18.7%) | 37 (21.8%) | 15 (14.9%) | |
| Missing | 2 | ||||
| 1 | 21 (5.3%) | 7 (5.2%) | 6 (3.6%) | 8 (8.1%) | |
| 2 | 299 (74.9%) | 86 (64.2%) | 131 (78.9%) | 82 (82.8%) | |
| 3 | 79 (19.8%) | 41 (30.6%) | 29 (17.5%) | 9 (9.1%) | |
| Missing | 13 | ||||
| 0.21 | |||||
| No | 273 (72.8%) | 84 (67.2%) | 120 (76.4%) | 69 (74.2%) | |
| Yes | 102 (27.2%) | 41 (32.8%) | 37 (23.6%) | 24 (25.8%) | |
| Missing | 37 | ||||
| 0.576 | |||||
| No | 328 (84.6%) | 110 (87.3%) | 135 (82.8%) | 83 (84.7%) | |
| Yes | 59 (15.4%) | 16 (12.7%) | 28 (17.2%) | 15 (15.3%) | |
| Missing | 25 | ||||
| 0.43 | |||||
| No | 298 (77.0%) | 92 (73.0%) | 129 (79.1%) | 77 (78.6%) | |
| Yes | 89 (23.0%) | 34 (27.0%) | 34 (20.9%) | 21 (21.4%) | |
| Missing | 25 | ||||
| 0.543 | |||||
| No | 332 (86.0%) | 109 (86.5%) | 136 (84.0%) | 87 (88.8%) | |
| Yes | 54 (14.0%) | 17 (13.5%) | 26 (16.0%) | 11 (11.2%) | |
| Missing | 26 | ||||
| 0.238* | |||||
| Capecitabine | 1 (0.2%) | 0 | 0 | 1 (1.0%) | |
| FOLFOX | 137 (33.6%) | 40 (29.0%) | 64 (38.1%) | 33 (32.4%) | |
| CAPOX | 270 (66.2%) | 98 (71.0%) | 104 (61.9%) | 68 (66.7%) | |
| Missing | 4 | ||||
| N/A | |||||
| No | 279 (76.9%) | 119 (99.2%) | 147 (97.4%) | 13 (14.1%) | |
| Yes | 84 (23.1%) | 1 (0.8%) | 4 (2.6%) | 79 (85.9%) | |
| Missing | 49 |
*1 patient with Capecitabine was excluded from the estimation of p-value.
Abbreviations: IQR: interquartile range, LVI: lymphovascular invasion, n: number, No: number, N/A: not applicable, PNI: perineural invasion, PS: performance status, SD: standard deviation.
IHC and NGS parameters in the entire cohort and by tumor location (right colon, left colon, rectum)
| Parameters* | Entire cohort (n=412) | Right colon (n=139) | Left colon (n=171) | Rectum (n=102) | p-value | |
|---|---|---|---|---|---|---|
| Deficiency | 40 (11.1%) | 31 (25.8%) | 6 (4.0%) | 3 (3.3%) | ||
| Proficiency | 320 (88.9%) | 89 (74.2%) | 144 (96.0%) | 87 (96.7%) | ||
| Missing | 52 | |||||
| High^ | 118 (28.6%) | 57 (41.0%) | 32 (18.7%) | 29 (28.4%) | ||
| Other^ | 294 (71.4%) | 82 (59.0%) | 139 (81.3%) | 73 (71.6%) | ||
| No | 321 (92.5%) | 99 (86.8%) | 141 (95.3%) | 81 (95.3%) | ||
| Yes | 26 (7.5%) | 15 (13.2%) | 7 (4.7%) | 4 (4.7%) | ||
| No | 158 (45.5%) | 61 (53.5%) | 54 (36.5%) | 43 (50.6%) | ||
| Yes | 189 (54.5%) | 53 (46.5%) | 94 (63.5%) | 42 (49.4%) | ||
| No | 309 (89.0%) | 104 (91.2%) | 138 (93.2%) | 67 (78.8%) | ||
| Yes | 38 (11.0%) | 10 (8.8%) | 10 (6.8%) | 18 (21.2%) | ||
| No | 321 (92.5%) | 107 (93.9%) | 141 (95.3%) | 73 (85.9%) | ||
| Yes | 26 (7.5%) | 7 (6.1%) | 7 (4.7%) | 12 (14.1%) | ||
| No | 284 (81.8%) | 84 (73.7%) | 129 (87.2%) | 71 (83.5%) | ||
| Yes | 63 (18.2%) | 30 (26.3%) | 19 (12.8%) | 14 (16.5%) | ||
*analysis was performed in informative samples.
Abbreviations: IHC: immunohistochemistry, IQR: interquartile range, MMR: mismatch repair, n: number, MUT: mutation, NGS: next-generation sequencing, N/A: not applicable, SD: standard deviation; ^: High: high CD8+ density, stromal AND intratumoral (in direct contact with cancer cells); Other: only stromal high OR only intratumoral high OR none high.
Figure 2Map of pathogenic mutations in 332 CRC
(A) Out of 1713 pathogenic mutations, 32% were nonsense or frameshifts in tumor suppressors, while missense mutations were dominant in known oncogenes. We did not apply the classification of hypermutated and non-hypermutated tumors because we used a 59-gene panel only. However, it is apparent that most tumors (75%) carried more than 1 pathogenic mutation, the most frequent combination being APC & TP53 in 1/3 of tumors, co-mutated with KRAS in ¼ of the cases, while 10% of tumors carried more than 10 pathogenic mutations. Despite that the applied reading depth was very high in our cases (>1000X, compared to <50X in whole genome sequencing), the 4 most frequently mutated genes are in line with previous publications. The high incidence of BRCA1, PTEN, CDH1 and BRCA2 mutations is most probably a result of high reading depth and over-representation of these genes in the custom panel. Red dots: genes with site-specific differences in the distribution of pathogenic mutations. (B) Demonstrates the actual number of tumors with pathogenic mutations in the presented genes. The number of tumors with pathogenic mutations is shown for the 15 most frequently affected genes. Blue bars correspond to the number of pathogenic mutations per gene; tumor suppressor genes, e.g., APC, TP53, occasionally carried multiple mutations per tumor, which was not observed for oncogenes, e.g., KRAS, BRAF. (C) Comparison of mutation numbers in MMR-D and MMR-P tumors. Although MMR-D were in general richer in mutations compared to MMR-P tumors, MMR-P tumors with mutations in MMR genes (red dots) exhibited higher mutation numbers compared to MMR-D, probably because of co-mutated pathways. Green dots: four MMR-D tumors with concordant MMR gene mutation status. Blue lines: mean values.
Figure 3Prognostic significance of (A) high CD8+ density; (B and C) BRCA1 and ARID1A pathogenic mutations.
Figure 4Associations between DFS and relevant clinicopathological, mutational and immunophenotypic parameters
Figure 1REMARK diagram
NGS: next generation sequencing; MMR: mismatch repair; MMR-P and MMR-D: proficient and deficient, respectively.