Currently favored sampling practices for tumor sequencing can produce optimal results in the clinical setting

Postzygotic mutations and where to find them - Recent advances and future implications in the field of non-neoplastic somatic mosaicism

The technological progress of massively parallel sequencing (MPS) has triggered a remarkable development in the research on postzygotic mutations. Although the overwhelming majority of studies in the field focus on oncogenesis, non-neoplastic diseases are attracting more and more attention. The aim of this review was to summarize some of the most recent findings in the field of somatic mosaicism in diseases other than neoplastic events. We discuss the abundance and role of postzygotic mutations, with a special emphasis on disorders which occur only in a mosaic form (obligatory mosaic diseases; OMDs). Based on the list of OMDs compiled from the published literature and three databases (OMIM, Orphanet and MosaicBase), we demonstrate the prevalence of cancer-related genes across OMDs and suggest other sources to further explore OMDs and OMD-related genes. Additionally, we comment on some practical aspects related to mosaic diseases, such as approaches to tissue sampling, the MPS coverage required to detect variants at a very low frequency, as well as on bioinformatic and molecular tools dedicated to detect somatic mutations in MPS data.

Genomics of Clear-cell Renal Cell Carcinoma: A Systematic Review and Meta-analysis

CONTEXT

Although antiangiogenic treatments and immunotherapies have significantly improved the prognosis of metastatic renal cell carcinoma (RCC), many patients will develop resistance, leading to treatment failure. Genetic tumor heterogeneity is a major cause of this resistance.

OBJECTIVE

To perform a meta-analysis of genomic data for clear-cell RCC obtained from primary tumors and metastases to assess the prevalence of gene mutations and copy number alterations (CNAs).

EVIDENCE ACQUISITION

Articles were selected from Medline and Embase libraries using the search algorithm ("Kidney Neoplasms"[Mesh] OR "Renal Cell Carcinoma") AND ("Genomics"[Mesh] OR "Mutation") from January 1999 to February 2021. A critical review was conducted according to the Preferred Reporting Items for Systematic Review and Meta-Analysis (PRISMA) statement. Ninety-three publications were selected for inclusion in this meta-analysis.

EVIDENCE SYNTHESIS

Our meta-analysis included a total 14 696 patients, 14 299 primary tumor samples, and 969 metastatic samples. We evaluated the overall and subgroup prevalence of gene mutations and CNAs, including comparisons between primary tumors and metastases. In particular, for metastases we observed that the mutation prevalence was significantly more marked for ten genes compared to primary tumors, with no or little heterogeneity across studies. The VHL mutation prevalence increased significantly from 64% in primary tumors to 75% in metastases (p < 0.001). There was a significant increase in CNA prevalence from primary tumors to metastases for chromosomes 1p36.11, 9p21.3, and 18 in terms of losses, and for chromosomes 1q21.3, 7q36.3, 8q, and 20q11.21 in terms of gains. CDKN2A, also called p16 and involved in cell-cycle progression, is located at the 9p21.3 locus and was lost in 76% of metastatic samples. ASXL1, located on 20p11.21 and amplified in 50% of metastatic RCCs compared to 21% of primary tumors (p < 0.001), is closely linked to BAP1 function.

CONCLUSIONS

Our results underline the added value of preferential biopsies on RCC metastases to fully explore the biology of metastatic disease for therapeutic purposes.

PATIENT SUMMARY

We reviewed the literature on genetic mutations in primary tumors and metastatic lesions in kidney cancer. Our pooled results for all the relevant studies show a higher level of mutations in metastases than in primary tumors. This highlights the importance of taking biopsies of metastases to analyze genetic mutations and potentially guide selection of the most suitable treatment strategy.

Comparative Assessment of Diagnostic Homologous Recombination Deficiency associated mutational signatures in ovarian cancer

BACKGROUND

Homologous recombination (HR) deficiency is one of the key determinants of PARP inhibitor response in ovarian cancer, and its accurate detection in tumor biopsies is expected to improve the efficacy of this therapy. Since HR deficiency induces a wide array of genomic aberrations, mutational signatures may serve as a companion diagnostic to identify PARP inhibitor responsive cases.

METHODS

From the TCGA whole exome sequencing data we extracted different types of mutational signature-based HR deficiency measures, such as the HRD score, genome-wide LOH and HRDetect trained on ovarian and breast cancer specific sequencing data. We compared their performance to identify BRCA1/2 deficient cases in the TCGA ovarian cancer cohort and predict survival benefit in platinum treated, BRCA1/2 wild type ovarian cancer.

RESULTS

We found that the HRD score, which is based on large chromosomal alterations alone, performed similarly well to an ovarian cancer specific HRDetect, which incorporates mutations on a finer scale as well (AUC=0.823 versus AUC=0.837). In an independent cohort these two methods were equally accurate predicting long term survival after platinum treatment (AUC=0.787 versus AUC=0.823). We also found that HRDetect trained on ovarian cancer was more accurate than HRDetect trained on breast cancer data (AUC=0.837 versus AUC=0.795, p=0.0072).

CONCLUSION

When WES data are available, methods that quantify only large chromosomal alterations such as the HRD score and HRDetect that captures a wider array of HR deficiency induced genomic aberrations are equally efficient identifying HR deficient ovarian cancer cases.