The recent successes of genome-wide expression profiling in biology tend to overlook the power of genetics. We here propose a merger of genomics and genetics into ‘genetical genomics’. This involves expression profiling and marker-based fingerprinting of each individual of a segregating population, and exploits all the statistical tools used in the analysis of quantitative trait loci. Genetical genomics will combine the power of two different worlds in a way that is likely to become instrumental in the further unravelling of metabolic, regulatory and developmental pathways.

Genetical genomics : the added value from segregation

[What is a cost-benefit analysis?].

Algorithms and applications

Preoperative Prediction of Axillary Lymph Node Metastasis in Breast Carcinoma Using Radiomics Features Based on the Fat-Suppressed T2 Sequence.

Tumours with mutations in the BRCA1/BRCA2 genes have impaired double-stranded DNA break repair, compromised replication fork protection and increased sensitivity to replication blocking agents, a phenotype collectively known as ‘BRCAness’. Tumours with a BRCAness phenotype become dependent on alternative repair pathways that are error-prone and introduce specific patterns of somatic mutations across the genome. The increasing availability of next-generation sequencing data of tumour samples has enabled identification of distinct mutational signatures associated with BRCAness. These signatures reveal that alternative repair pathways, including Polymerase θ-mediated alternative end-joining and RAD52-mediated single strand annealing are active in BRCA1/2-deficient tumours, pointing towards potential therapeutic targets in these tumours. Additionally, insight into the mutations and consequences of unrepaired DNA lesions may also aid in the identification of BRCA-like tumours lacking BRCA1/BRCA2 gene inactivation. This is clinically relevant, as these tumours respond favourably to treatment with DNA-damaging agents, including PARP inhibitors or cisplatin, which have been successfully used to treat patients with BRCA1/2-defective tumours. In this review, we aim to provide insight in the origins of the mutational landscape associated with BRCAness by exploring the molecular biology of alternative DNA repair pathways, which may represent actionable therapeutic targets in in these cells.

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Shaping the BRCAness mutational landscape by alternative double-strand break repair, replication stress and mitotic aberrancies

Treatment with chemotherapy and immunotherapy at the time of COVID-19 vaccination may result in inadequate humoral responses.1Peeters M. Verbruggen L. Teuwen L. et al.Reduced humoral immune response after BNT162b2 coronavirus disease 2019 messenger RNA vaccination in cancer patients under antineoplastic treatment.ESMO Open. 2021; 6100274Abstract Full Text Full Text PDF Scopus (49) Google Scholar,2Oosting S.F. van der Veldt A.A.M. GeurtsvanKessel C.H. et al.mRNA-1273 COVID-19 vaccination in patients receiving chemotherapy, immunotherapy, or chemoimmunotherapy for solid tumours: a prospective, multicentre, non-inferiority trial.Lancet Oncol. 2021; 22: 1681-1691Abstract Full Text Full Text PDF PubMed Scopus (72) Google Scholar We and others demonstrated that a third vaccination increases serum SARS-CoV-2 specific antibody concentration, but little is known about long-term antibody concentrations and breakthrough infections in these patients.3Oosting S.F. van der Veldt A.A.M. Fehrmann R.S.N. et al.Immunogenicity after second and third mRNA-1273 vaccination doses in patients receiving chemotherapy, immunotherapy, or both for solid tumours.Lancet Oncol. 2022; 23: 833-835Abstract Full Text Full Text PDF PubMed Scopus (0) Google Scholar, 4Fendler A. Shephers S.T.C. Au L. et al.Immune responses following third COVID-19 vaccination are reduced in patients with hematological malignancies compared to patients with solid cancer.Cancer Cell. 2022; 40: 438Abstract Full Text Full Text PDF PubMed Scopus (0) Google Scholar, 5Ehmsen S. Asmussen A. Jeppesen S.S. et al.Antibody responses following third mRNA COVID-19 vaccination in patients with cancer and potential timing of a fourth vaccination.Cancer Cell. 2022; 40: 338-339Abstract Full Text Full Text PDF PubMed Scopus (15) Google Scholar Here, we report the 18-month data of the prospective multicenter VOICE trial (Figure S1, NCT04715438) of COVID-19 vaccination in patients treated for solid tumors with immunotherapy (cohort B), chemotherapy (cohort C), or chemoimmunotherapy (cohort D) compared to controls (cohort A). In the trial, participants received two mRNA-1273 vaccinations (100 μg intramuscularly) four weeks apart and a third vaccination if the initial response was inadequate. All participants had access to additional COVID-19 mRNA vaccinations in the national vaccination program. SARS-CoV-2-binding antibody concentrations were measured as previously described.2Oosting S.F. van der Veldt A.A.M. GeurtsvanKessel C.H. et al.mRNA-1273 COVID-19 vaccination in patients receiving chemotherapy, immunotherapy, or chemoimmunotherapy for solid tumours: a prospective, multicentre, non-inferiority trial.Lancet Oncol. 2021; 22: 1681-1691Abstract Full Text Full Text PDF PubMed Scopus (72) Google Scholar Breakthrough infections were assessed with 3-monthly questionnaires and with SARS-CoV-2 nucleoprotein-specific IgG antibody measurements. At 18 months, 112, 68, 97, and 36 participants were evaluable in cohorts A, B, C, and D, respectively (Figure S2). Participants received up to six vaccinations in total (Table S1). The high levels of binding antibody concentrations at one year were maintained at 18 months in all cohorts (Figure S3), and the geometric mean concentrations even slightly increased by 1.22, 1.53, 1.23, and 1.03 fold in cohorts A, B, C, and D, respectively. A SARS-CoV-2 infection in the previous 6 months was reported by 16.1% (n=18), 8.8% (n=6), 16.5% (n=16), and 8.3% (n=3) in cohorts A, B, C, and D (Table S2) and serological evidence of prior SARS-CoV-2 infection at 18 months was found in 26.8% (n=30), 17.6% (n=12), 21.7% (n=21), and 11.1% (n=4). Decision tree analysis identified the absence of serological evidence of a prior infection as the most important factor for lower SARS-CoV-2-binding antibody concentrations at 18 months. Other determinants were long interval since last vaccination, no prior infection based on questionnaires, and long interval since infection (Figure 1, S4). An increase in antibody concentration compared to previous measurement at one year was associated with a prior infection based on serology and time since last vaccination (Figure S5). Based on serology and the questionnaire, 121 participants did not have breakthrough infections nor had received additional vaccines in the last six months. The median reduction of SARS-CoV-2-binding antibody concentration from one year to 18 months in these 121 participants was 1618.2 BAU/ml. The geometric mean concentrations for these participants were 3571.3, 3394.1, 4188.3, and 1607.4 BAU/ml in cohorts A, B, C, and D, respectively at 18 months, compared to 5243, 3373, 6334, and 3055.7, respectively at one year. Our 18-month data show that patients treated with chemotherapy, immunotherapy, or chemoimmunotherapy for a solid tumor at the time of initial vaccination have sustained high SARS-CoV-2-binding antibody concentrations, similar to controls. Additional vaccinations and infections but not cancer treatment determine antibody response over time. These encouraging results can be used to develop future vaccination strategies for patients with solid tumors, not only for prevention of infectious diseases but also for the development of cancer vaccines. Download .docx (1.32 MB) Help with docx files 

http://www.esmoopen.com/article/S2059702923008335/pdf

Factors associated with long-term antibody response after COVID-19 vaccination in patients treated with systemic treatment for solid tumors

Background Oncogene-induced replication stress characterizes many aggressive cancers, including triple-negative breast cancer (TNBC). Several drugs are being developed that target replication stress, although it is unclear how tumors with high levels of replication stress can be identified. We aimed to develop a gene expression signature of oncogene-induced replication stress. Methods TNBC and non-transformed RPE1-TP53wt and RPE1-TP53mut cell lines were engineered to overexpress the oncogenes CDC25A, CCNE1 or MYC. DNA fiber analysis was used to measure replication kinetics. Analysis of RNA sequencing data of cell lines and patient-derived tumor samples (TCGA n=10,592) was used to identify differential gene expression. Immunohistochemical validation was conducted on breast cancer samples (n=330). Results RNA sequencing revealed 52 commonly upregulated genes after induction of CDC25A, CCNE1 or MYC in our cell line panel. Integration with gene expression data of TGCA samples with amplification of replication stress-inducing oncogenes (CDC25A, CCNE1, MYC, CCND1, MYB, MOS, KRAS, ERBB2, and E2F1), yielded a six-gene signature of oncogene-induced replication stress (NAT10, DDX27, ZNF48, C8ORF33, MOCS3, and MPP6). Expression of NAT10 in breast cancer samples was correlated with phospho-RPA (R=0.451, p=1.82×10−20) and γH2AX (R=0.304, p=2.95×10−9). Applying the oncogene-induced replication stress signature to patient samples (TCGA n=8,862 and GEO n=13,912) defined the replication stress landscape across 27 tumor subtypes, and identified diffuse large B cell lymphoma, ovarian cancer, TNBC and colorectal carcinoma as cancer subtypes with high levels of oncogene-induced replication stress. Conclusion We developed a gene expression signature of oncogene-induced replication stress, which may facilitate patient selection for agents that target replication stress.

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An mRNA expression-based signature for oncogene-induced replication-stress

http://www.cell.com/article/S2211124723006794/pdf

FIRRM/C1orf112 is synthetic lethal with PICH and mediates RAD51 dynamics.


 Mediator (MED) proteins typically assemble and recruit distal coactivators at binding sites of RNA polymerase II to help regulate a gene’s transcriptional output. The MED-kinase module consists of four subunits, MED12/12L, MED13/13L, CDK8/19 and Cyclin C, and reversibly interacts with the MED-core complex to function as a lineage-specific transcriptional activator. In particular, MED12 has been reported to recruit BRD4, FLI/ERG, CBP/p300, and GATA2 transcription factors on H3K27ac-enriched super-enhancer (SE) loci in hematopoietic stem and acute myeloid leukemia (AML) cells to maintain cell fate determination or leukemic growth respectively. Given the regulatory role MED12 in AML, there is a sustained interest in identifying targeted inhibitors against this MED-protein. Herein, we aimed to investigate if the oncogenic over-expression of MED12 is epigenetically regulated in AML. We analyzed the MED12 transcriptomic data in AML patients, belongs to 6 cytogenetic subgroups having chromosomal aberrations such as inv(16) (n=28), t(15;17) (n=37), t(8;21) (n=40), MLL-rearranged (n=38), AML-complex (n=48), and normal karyotype (n=351), compared to normal bone marrow (NBM) mononuclear cells (n=73), from the Microarray Innovations in Leukemia (MILE) study (Stage I). MED12 was found significantly (p<0.01) upregulated in AML subgroups, except for the AML-complex subgroup along 3 probe sets (211342_x_at, 203506_s_at, and 216071_x_at). The highest upregulation of MED12 was observed in the inv(16) subgroup having the mean differential expression of 0.78, followed by 0.57 in t(8;21) and 0.5 in t(15;17) subgroup, compared to NBM. Considering the fact that inv(16) and t(8;21) subgroups showed highest expression of the gene, and are categorized as the core-binding factor (CBF) AML-subgroups, we examined DNA-methylation and chromatin modifications of MED12 in patients [n=3 for inv(16) and n=1 for t(8;21)], based on the whole-genome bisulfite sequencing and chromatin immunoprecipitation sequencing data, as available at the BLUEPRINT epigenome, and DNAse sequencing (K562 cells) data at ENCODE. We observed DNAse hypersensitive peaks at the exon-26 and a region (229 bp) spanning the transcription start site (TSS) and upstream promoter of the gene, indication an open chromatin conformation. The TSS and upstream promoter also contained a broad H3K4me3 domain [1.7 kb in inv(16) and 1.2 kb in t(8;21)], with an overlapping hypomethylated CpG-island. Collectively, our findings suggest that MED12 oncogenic over-expression in CBF AML-subgroups are fostered by an epigenetically active promoter. Future studies will be aimed at understanding the impact of targeted perturbation of MED12 in the enhancer mechanism and sustenance of leukemic growth in CBF AML-subgroups.
 Citation Format: Samrat Roy Choudhury, Arkajyoti Bhattacharya. Oncogenic over-expression of MED12 is epigenetically fostered in the core-binding factor subgroups of acute myeloid leukemia. [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 4762.

Arkajyoti Bhattacharya

Papers

Factors associated with long-term antibody response after COVID-19 vaccination in patients treated with systemic treatment for solid tumors

An mRNA expression-based signature for oncogene-induced replication-stress

FIRRM/C1orf112 is synthetic lethal with PICH and mediates RAD51 dynamics.

Abstract 4762: Oncogenic over-expression of MED12 is epigenetically fostered in the core-binding factor subgroups of acute myeloid leukemia