Mutations in yeast Pcf11, a conserved protein essential for mRNA 3' end processing and transcription termination, elicit the Environmental Stress Response.

The Pcf11 protein is an essential subunit of the large complex that cleaves and polyadenylates eukaryotic mRNA precursor. It has also been functionally linked to gene-looping, termination of RNA Polymerase II (Pol II) transcripts, and mRNA export. We have examined a poorly characterized but conserved domain (amino acids 142-225) of the Saccharomyces cerevisiae  Pcf11 and found that while it is not needed for mRNA 3' end processing or termination downstream of the poly(A) sites of protein-coding genes, its presence improves the interaction with Pol II and the use of transcription terminators near gene promoters. Analysis of genome-wide Pol II occupancy in cells with Pcf11 missing this region, as well as Pcf11 mutated in the Pol II CTD Interacting Domain, indicates that systematic changes in mRNA expression are mediated primarily at the level of transcription. Global expression analysis also shows that a general stress response, involving both activation and suppression of specific gene sets known to be regulated in response to a wide variety of stresses, is induced in the two pcf11 mutants, even though cells are grown in optimal conditions. The mutants also cause an unbalanced expression of cell wall-related genes that does not activate the Cell Wall Integrity pathway but is associated with strong caffeine sensitivity. Based on these findings, we propose that Pcf11 can modulate the expression level of specific functional groups of genes in ways that do not involve its well-characterized role in mRNA 3' end processing.

Tumor Mutational Burden From Tumor-Only Sequencing Compared With Germline Subtraction From Paired Tumor and Normal Specimens.

Importance: Tumor mutation burden (TMB) is an emerging factor associated with survival with immunotherapy. When tumor-normal pairs are available, TMB is determined by calculating the difference between somatic and germline sequences. In the case of commonly used tumor-only sequencing, additional steps are needed to estimate the somatic alterations. Computational tools have been developed to determine germline contribution based on sample copy state, purity estimates, and occurrence of the variant in population databases; however, there is potential for sampling bias in population data sets. Objective: To investigate whether tumor-only filtering approaches overestimate TMB. Design, Setting, and Participants: This was a retrospective cohort study of 50 tumor samples from 10 different tumor types. A 595-gene panel test was used to assess TMB by adding all missense, indels, and frameshift variants with an allelic fraction of at least 5% and coverage of at least 100× within each tumor. Tumor-only TMB was evaluated against the criterion standard of matched germline-subtracted TMB at 3 levels. Level 1 removed all the tumor-only variants with allelic fraction of at least 1% in the Exome Aggregation Consortium database (with the Cancer Genome Atlas cohort removed). Level 2 removed all variants observed in population databases, simulating a naive approach of removing germline variation. Level 3 used an internal tumor-only pipeline for calculating TMB. These specimens were processed with a commercially available panel, and results were analyzed at the Mayo Clinic. Data were analyzed between December 1, 2018, and May 28, 2019. Main Outcomes and Measures: Tumor mutation burden per megabase (Mb) as determined by 3 levels of filtering and germline subtraction. Results: There were significantly higher estimates of TMB with level 1 (median [range] mutations per Mb, 28.8 [17.5-67.1]), level 2 (median [range] mutations per Mb, 20.8 [10.4-30.8]), and level 3 (median [range] mutations per Mb, 3.8 [0.8-12.1]) tumor-only filtering approaches than those determined by germline subtraction (median [range] mutations per Mb, 1.7 [0.4-9.2]). There were no strong associations between TMB estimates and tumor-germline TMB for level 1 filtering (r = 0.008; 95% CI, -0.004 to 0.020), level 2 filtering (r = 0.018; 95% CI, 0.003 to 0.033), or level 3 filtering (r = 0.54; 95% CI, 0.36 to 0.68). Conclusions and Relevance: The findings of this study indicate that tumor-only approaches that filter variants in population databases can overestimate TMB compared with germline subtraction methods. Despite improved association with more stringent filtering approaches, these falsely elevated estimates may result in the inappropriate categorization of tumor specimens and negatively affect clinical trial results and patient outcomes.

Integrated genomic profiling expands clinical options for patients with cancer.

Genomic analysis of paired tumor-normal samples and clinical data can be used to match patients to cancer therapies or clinical trials. We analyzed 500 patient samples across diverse tumor types using the Tempus xT platform by DNA-seq, RNA-seq and immunological biomarkers. The use of a tumor and germline dataset led to substantial improvements in mutation identification and a reduction in false-positive rates. RNA-seq enhanced gene fusion detection and cancer type classifications. With DNA-seq alone, 29.6% of patients matched to precision therapies supported by high levels of evidence or by well-powered studies. This proportion increased to 43.4% with the addition of RNA-seq and immunotherapy biomarker results. Combining these data with clinical criteria, 76.8% of patients were matched to at least one relevant clinical trial on the basis of biomarkers measured by the xT assay. These results indicate that extensive molecular profiling combined with clinical data identifies personalized therapies and clinical trials for a large proportion of patients with cancer and that paired tumor-normal plus transcriptome sequencing outperforms tumor-only DNA panel testing.

Considerations for clinical curation, classification, and reporting of low-penetrance and low effect size variants associated with disease risk.

PURPOSE: Clinically relevant variants exhibit a wide range of penetrance. Medical practice has traditionally focused on highly penetrant variants with large effect sizes and, consequently, classification and clinical reporting frameworks are tailored to that variant type. At the other end of the penetrance spectrum, where variants are often referred to as "risk alleles," traditional frameworks are no longer appropriate. This has led to inconsistency in how such variants are interpreted and classified. Here, we describe a conceptual framework to begin addressing this gap. METHODS: We used a set of risk alleles to define data elements that can characterize the validity of reported disease associations. We assigned weight to these data elements and established classification categories expressing confidence levels. This framework was then expanded to develop criteria for inclusion of risk alleles on clinical reports. RESULTS: Foundational data elements include cohort size, quality of phenotyping, statistical significance, and replication of results. Criteria for determining inclusion of risk alleles on clinical reports include presence of clinical management guidelines, effect size, severity of the associated phenotype, and effectiveness of intervention. CONCLUSION: This framework represents an approach for classifying risk alleles and can serve as a foundation to catalyze community efforts for refinement.

Exome Sequencing-Based Screening for BRCA1/2 Expected Pathogenic Variants Among Adult Biobank Participants.

Importance: Detection of disease-associated variants in the BRCA1 and BRCA2 (BRCA1/2) genes allows for cancer prevention and early diagnosis in high-risk individuals. Objectives: To identify pathogenic and likely pathogenic (P/LP) BRCA1/2 variants in an unselected research cohort, and to characterize the features associated with P/LP variants. Design, Setting, and Participants: This is a cross-sectional study of adult volunteers (n = 50 726) who underwent exome sequencing at a single health care system (Geisinger Health System, Danville, Pennsylvania) from January 1, 2014, to March 1, 2016. Participants are part of the DiscovEHR cohort and were identified through the Geisinger MyCode Community Health Initiative. They consented to a research protocol that included sequencing and return of actionable test results. Clinical data from electronic health records and clinical visits were correlated with variants. Comparisons were made between those with (cases) and those without (controls) P/LP variants in BRCA1/2. Main Outcomes: Prevalence of P/LP BRCA1/2 variants in cohort, proportion of variant carriers not previously ascertained through clinical testing, and personal and family history of relevant cancers among BRCA1/2 variant carriers and noncarriers. Results: Of the 50 726 health system patients who underwent exome sequencing, 50 459 (99.5%) had no expected pathogenic BRCA1/2 variants and 267 (0.5%) were BRCA1/2 carriers. Of the 267 cases (148 [55.4%] were women and 119 [44.6%] were men with a mean [range] age of 58.9 [23-90] years), 183 (68.5%) received clinically confirmed results in their electronic health record. Among the 267 participants with P/LP BRCA1/2 variants, 219 (82.0%) had no prior clinical testing, 95 (35.6%) had BRCA1 variants, and 172 (64.4%) had BRCA2 variants. Syndromic cancer diagnoses were present in 11 (47.8%) of the 23 deceased BRCA1/2 carriers and in 56 (20.9%) of all 267 BRCA1/2 carriers. Among women, 31 (20.9%) of 148 variant carriers had a personal history of breast cancer, compared with 1554 (5.2%) of 29 880 noncarriers (odds ratio [OR], 5.95; 95% CI, 3.88-9.13; P < .001). Ovarian cancer history was present in 15 (10.1%) of 148 variant carriers and in 195 (0.6%) of 29 880 variant noncarriers (OR, 18.30; 95% CI, 10.48-31.4; P < .001). Among 89 BRCA1/2 carriers without prior testing but with comprehensive personal and family history data, 44 (49.4%) did not meet published guidelines for clinical testing. Conclusions and Relevance: This study found that compared with previous clinical care, exome sequencing-based screening identified 5 times as many individuals with P/LP BRCA1/2 variants. These findings suggest that genomic screening may identify BRCA1/2-associated cancer risk that might otherwise remain undetected within health care systems and may provide opportunities to reduce morbidity and mortality in patients.

The current state of clinical interpretation of sequence variants.

Accurate and consistent variant classification is required for Precision Medicine. But clinical variant classification remains in its infancy. While recent guidelines put forth jointly by the American College of Medical Genetics and Genomics (ACMG) and Association of Molecular Pathology (AMP) for the classification of Mendelian variants has advanced the field, the degree of subjectivity allowed by these guidelines can still lead to inconsistent classification across clinical molecular genetic laboratories. In addition, there are currently no such guidelines for somatic cancer variants, only published institutional practices. Additional variant classification guidelines, including disease- or gene-specific criteria, along with inter-laboratory data sharing is critical for accurate and consistent variant interpretation.

The C terminus of Pcf11 forms a novel zinc-finger structure that plays an essential role in mRNA 3'-end processing.

3'-End processing of pre-mRNAs prior to packaging and export to the cytoplasm of the mature transcript is a highly regulated process executed by several tens of protein factors that recognize poorly conserved RNA signals. Among them is Pcf11, a highly conserved, multidomain protein that links transcriptional elongation, 3'-end processing, and transcription termination. Here we report the structure and biochemical function of Pcf11's C-terminal domain, which is conserved from yeast to humans. We identify a novel zinc-finger fold, resembling a trillium flower. Structural, biochemical, and genetic analyses reveal a highly conserved surface that plays a critical role in both cleavage and polyadenylation. These findings provide further insight into this important protein and its multiple functional roles during cotranscriptional RNA processing.

DNA damage induces targeted, genome-wide variation of poly(A) sites in budding yeast.

Systemic response to DNA damage and other stresses is a complex process that includes changes in the regulation and activity of nearly all stages of gene expression. One gene regulatory mechanism used by eukaryotes is selection among alternative transcript isoforms that differ in polyadenylation [poly(A)] sites, resulting in changes either to the coding sequence or to portions of the 3' UTR that govern translation, stability, and localization. To determine the extent to which this means of regulation is used in response to DNA damage, we conducted a global analysis of poly(A) site usage in Saccharomyces cerevisiae after exposure to the UV mimetic, 4-nitroquinoline 1-oxide (4NQO). Two thousand thirty-one genes were found to have significant variation in poly(A) site distributions following 4NQO treatment, with a strong bias toward loss of short transcripts, including many with poly(A) sites located within the protein coding sequence (CDS). We further explored one possible mechanism that could contribute to the widespread differences in mRNA isoforms. The change in poly(A) site profile was associated with an inhibition of cleavage and polyadenylation in cell extract and a decrease in the levels of several key subunits in the mRNA 3'-end processing complex. Sequence analysis identified differences in the cis-acting elements that flank putatively suppressed and enhanced poly(A) sites, suggesting a mechanism that could discriminate between variable and constitutive poly(A) sites. Our analysis indicates that variation in mRNA length is an important part of the regulatory response to DNA damage.