Vanderbilt University School of Medicine, Nashville, TN;
Michael Brian LaPelusa , Christopher G Cann , Cathy Eng
Background: The feasibility of identifying genomic alterations via next-generation sequencing (NGS) of peripheral blood (PB) to spare patients an invasive biopsy is an active area of investigation. High concordance of mutations between tissue and PB has been observed in several cancer types. However, the concordance between tissue and PB in patients with SCCA is unknown. Methods: We identified 11 patients with SCCA who had NGS (TEMPUS) performed on tissue and PB between 2017 - 2022. The IRB at Vanderbilt-Ingram Cancer Center approved this study. Results: See Table. Conclusions: In 6 of the 11 patients, concordant genomic alterations found in tissue were also identified in PB. More patients with anal cancer should be studied to better understand this phenomenon and the impact of therapy on ctDNA kinetics.
Patient | Sample | Collection interval (days) | Somatic – potentially actionable (variant allele frequency (VAF), if reported) | Somatic – biologically relevant (VAF) | Variants of unknown significance (VAF) |
---|---|---|---|---|---|
1 | Anus | T | -CDKN2A (47.4%) -TP53 (45.9%) -CCND1 | -TERT (38.5%) -FGF19 -FGF3 -FGF4 | -MTHFR (53.1%) -WEE1 (34.5%) -CBLB (7.9%) |
PB | T + 643 | -TP53 (1.3%) | -TERT (3.6%) -CDKN2A (1.4%) | -ATM (0.4%) | |
2 | Anus | T | -MAPK1 (15.0%) | -ARID2 (15.1%) -FANCA (11.2%) | -SMAD3 (17.4%) -MSH2 (16.9%) -HIST1H1E (15.8%) -EPHA2 (15.4%) -LMNA (14.4%) -FANCA (11.1%) -DYNC2H1 (7.3%) -SETD2 (6.9%) |
PB | T + 414 | -MAPK1 (7.3%) | None | -KDR (50.4%) -SDHA (46.8%) -MSH2 (6.9%) | |
3 | Anus | T | None | -FAT1 (22.2%) -CASP8 -ERCC3 -FHIT -FOXP1 -LRP1B | -SYNE1 (22.2%) -PTPN11 (18.1%) |
PB | T + 484 | None | -MYC | -HNF1A (57.4%) | |
4 | Lung | T | -PIK3CA (37.0%) | -CYLD (64.1%) -CREBBP (21.7%) -EBF1 | -KIF1B (35.0%) -CREBBP (25.7%) |
PB | T + 1057 | None | None | None | |
5 | Pelvis | T | -PIK3CA (18.6%) | -STK11 (38.0%) -BCL118 -SLIT2 | -STK11 (36.0%) -TPM1 (33.7%) -AMER1 (24.1%) -CTRC (22.3%) -RAD51B (19.7%) -ETS2 (18.7%) |
PB | T + 763 | None | -STK11 (32.0%) | -STK11 (34.8%) -TPM1 (26.9%) -CTRC (20.8%) -AMER1 (17.9%) -CD40 (9.7%) -RAD21 (6.7%) -CHD7 (6.4%) | |
6 | Brain | T | None | -CYLD (83.4%) | -SETD2 (84.2%) -SEC63 (45.6%) -AGO1 (40.6%) -ATRX (34.7%) |
PB | T + 763 | None | -SDHA (1.3%) | -FGFR2 (49.7%) -MAP2K1 (0.9%) | |
7 | Anus | T | None | -APC | -APOB (25.1%) -ROS1 (21.8%) -GRM3 (20.1%) -MYH11 (20.0%) -PMS2 (19.4%) |
Blood | T + 369 | None | None | None | |
8 | Anus | T | -PIK3CA (22.8%) | -KMT2D (43.5%) -B2M | -PHOX2B (85.3%) -HSD3B1 (38.8%) |
PB | T + 205 | -PIK3CA (24.5%) | None | -PBRM1 (85.1%) -DDR2 (49.9%) -MYCN (48.6%) -APC (12.1%) -SDHA (0.9%) -CDKN2A (0.2%) | |
9 | Anus | T | None | -CYLD (23.0%) | -UBC (26.1%) -RAD51C (24.5%) -JAK2 (17.9%) |
PB | T + 989 | None | None | -RAD51C (40.9%) -JAK2 (33.8%) -MTOR (13.9%) -PMS2 (5.7%) -BRCA1 (4.8%) | |
10 | Anus | T | -PIK3CA (45.8%) -FBXW7 (14.3%) -CDKN2A | -CDKN2B -SOX2 | -SDHC (18.8%) -EPHA2 (14.9%) -ABL1 (13.9%) -CD70 (12.3%) -SMARCA1 (11.7%) |
PB | T + 763 | -PIK3CA (14.9%) | -FBXW7 (28.7%) | -ERBB2 (28.2%) | |
11 | Anus | T | -KMT2C/MLLC (18.8%) -PIK3CA | -EP300 (32.8%) -CREBBP (28.4%) -ASXL1 (7.0%) -BCL6 -MCL1 -SOX2 | -NSD1 (16.7%) -LRP1B (13.7%) -DNM2 (7.1%) -KLHL6 (6.1%) -ERBB4 (5.7%) |
PB | T + 1713 | None | None | None |
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