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. 2024 Mar-Apr;21(2):203-212.
doi: 10.21873/cgp.20441.

Impact of Tumor Grade Distribution on Genetic Alterations in Clear Cell Renal Cell Carcinoma and Prostate Cancer

Kosuke Mizutani  1   2 , Seiji Sugiyama  3 , Koji Kameyama  4 , Shingo Kamei  4 , Shigeaki Yokoi  4 , Akemi Morikawa  5 , Makoto Takeuchi  5 , Kensaku Seike  6 , Toru Yamada  7 , Hidetoshi Ehara  8 , Seiya Sawada  2 , Kouseki Hirade  2 , Hirohito Furuta  9 , Kengo Matsunaga  3 , Tetsuya Yamada  3 , Ippei Sakamoto  10 , Yasutaka Kato  11 , Hiroshi Nishihara  11 , Satoshi Ishihara  4   2 , Takashi Deguchi  4
Affiliations

Impact of Tumor Grade Distribution on Genetic Alterations in Clear Cell Renal Cell Carcinoma and Prostate Cancer

Kosuke Mizutani et al. Cancer Genomics Proteomics. 2024 Mar-Apr.

Abstract

Background/aim: A genomic analysis based on next-generation sequencing is important for deciding cancer treatment strategies. Cancer tissue sometimes displays intratumor heterogeneity and a pathologic specimen may contain more than two tumor grades. Although tumor grades are very important for the cancer prognosis, the impact of higher tumor grade distribution in a specimen used for a genomic analysis is unknown.

Patients and methods: We retrospectively analyzed the data of 61 clear cell carcinoma and 46 prostate cancer patients that were diagnosed between December 2018 and August 2022 using the GeneRead Human Comprehensive Cancer Panel or SureSelect PrePool custom Tier2. Genome annotation and curation were performed using the GenomeJack software.

Results: Tumor mutation burden (TMB) was increased in proportion to the higher tumor grade distribution in grade 2 clear cell renal cell carcinoma (ccRCC). In PC, Grade Group 3/4 specimens that included an increased distribution of Gleason pattern 4 had more frequent gene mutations.

Conclusion: Our results suggest the importance of selecting the maximum distribution of higher tumor grade areas to obtain results on the precise gene alterations for genomics-focused treatments.

Keywords: Tumor grade distribution; cancer panel test; genetic alteration; intratumor heterogeneity.

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Conflict of interest statement

The Authors declare that they have no competing interests.

Figures

Figure 1
Figure 1. Patient selection and composition of the clear cell renal cell carcinoma (ccRCC) and prostate cancer (PC) cohorts. 69 RCCs and 56 PCs were tested by the cancer panels. After exclusion of ineligible participants, data from 61 RCC and 46 PC were analyzed in this study.
Figure 2
Figure 2. Representative data of tumor specimens. A and B: Representative data from a clear cell renal cell carcinoma (ccRCC) specimen diagnosed as grade 2. Grade 1 was dominant in the sample area selected for the cancer panel test (A). Grade 2 was dominant in the sample area selected for the cancer panel test (B). The area enclosed by the black line was macro-dissected and used for DNA extraction following the cancer panel test. The area enclosed by the blue line was grade 1 ccRCC dominant area, while that enclosed by the red line was grade 2 ccRCC dominant area. C and D: Representative data of a prostate cancer (PC) specimen diagnosed as grade group 2/3. Gleason pattern 3 was dominant in the sample area selected for the cancer panel test (C). Gleason pattern 4 was dominant in the sample area selected for the cancer panel test (D). The area enclosed by the black line was macro-dissected and used for DNA extraction following the cancer panel test. The area enclosed by the blue line was Gleason pattern 3 dominant area, while the area enclosed by the red line was Gleason pattern 4 dominant area.
Figure 3
Figure 3. The tumor mutation burden (TMB) and copy number alteration (CNA) count in clear cell renal cell carcinoma (ccRCC). A: TMB in grade 1, grade 2 and grade 3/4. B: TMB in cases with 20-40% grade 2 distribution area and 50-100%. C: The correlation between TMB and the ratio of the G2 distribution area in G2 ccRCC. D: The CNA count in grade 1, grade 2 and grade 3/4. E: CNA count in cases with 20-40% grade 2 distribution area and 50-100%. F: The correlation between CNA count and the ratio of the G2 distribution area in G2 ccRCC.
Figure 4
Figure 4. Gene mutations in clear cell renal cell carcinoma (ccRCC). A: The numbers of cases with or without gene mutation in each tumor grade of ccRCC. The statistical value was calculated using Fisher’s exact test with the Bonferroni post hoc test. B: The frequency of cases with VHL mutation or a mutation of BAP1, PBRM1, SETD2, or PTEN in each tumor grade of ccRCC. C: The frequency of cases with VHL mutation or a mutation of BAP1, PBRM1, SETD2, or PTEN in specimens with ≤20% grade 2 distribution and ≥30% grade 2 distribution.
Figure 5
Figure 5. Tumor mutation burden (TMB) and copy number alteration (CNA) count of prostate cancer (PC). A: TMB in PC diagnosed as grade group 1-5. B: The correlation between TMB and grade group. C: The CNA count in PC diagnosed as grade group 1-5. D: The correlation between CNA count and grade group. E: The correlation between TMB and the ratio of Gleason pattern 4 distribution area in G3/4 PC. F: The correlation between CNA count and the ratio of Gleason pattern 4 distribution area in G3/4 PC.
Figure 6
Figure 6. Gene mutations in prostate cancer (PC). A: The number of cases with or without gene mutation in each grade group of PC. B: The number of cases with or without gene mutation in specimens with <50% Gleason pattern 3, with ≥50% Gleason pattern 4, or with any amount of Gleason pattern 5. The statistical value was calculated using Fisher’s exact test with the Bonferroni post hoc test. C: The frequency of cases with mutation in specimens with different distribution ratios of Gleason pattern 4 in GG2/3. D: The number of cases with or without gene mutation in GG2/3 specimens with <70% Gleason pattern 4 and ≥70% Gleason pattern 4. The statistical value was calculated using Fisher’s exact test.
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