PITX1 is a regulator of TERT expression in prostate cancer with prognostic power

Simple Summary Most prostate cancer is of an indolent form and is curable. However, some prostate cancer belongs to rather aggressive subtypes leading to metastasis and death, and immediate therapy is mandatory. However, for these, the therapeutic options are highly invasive, such as radical prostatectomy, radiation or brachytherapy. Hence, a precise diagnosis of these tumor subtypes is needed, and the thus far applied diagnostic means are insufficient for this. Besides this, for their endless cell divisions, prostate cancer cells need the enzyme telomerase to elongate their telomeres (chromatin endings). In this study, we developed a gene regulatory model based on large data from transcription profiles from prostate cancer and chromatin-immuno-precipitation studies. We identified the developmental regulator PITX1 regulating telomerase. Besides observing experimental evidence of PITX1′s functional role in telomerase regulation, we also found PITX1 serving as a prognostic marker, as concluded from an analysis of more than 15,000 prostate cancer samples. Abstract The current risk stratification in prostate cancer (PCa) is frequently insufficient to adequately predict disease development and outcome. One hallmark of cancer is telomere maintenance. For telomere maintenance, PCa cells exclusively employ telomerase, making it essential for this cancer entity. However, TERT, the catalytic protein component of the reverse transcriptase telomerase, itself does not suit as a prognostic marker for prostate cancer as it is rather low expressed. We investigated if, instead of TERT , transcription factors regulating TERT may suit as prognostic markers. To identify transcription factors regulating TERT , we developed and applied a new gene regulatory modeling strategy to a comprehensive transcriptome dataset of 445 primary PCa. Six transcription factors were predicted as TERT regulators, and most prominently, the developmental morphogenic factor PITX1. PITX1 expression positively correlated with telomere staining intensity in PCa tumor samples. Functional assays and chromatin immune-precipitation showed that PITX1 activates TERT expression in PCa cells. Clinically, we observed that PITX1 is an excellent prognostic marker, as concluded from an analysis of more than 15,000 PCa samples. PITX1 expression in tumor samples associated with (i) increased Ki67 expression indicating increased tumor growth, (ii) a worse prognosis, and (iii) correlated with telomere length

Linking aberrant chromatin features in chronic lymphocytic leukemia to transcription factor networks

In chronic lymphocytic leukemia (CLL), a diverse set of genetic mutations is embedded in a deregulated epigenetic landscape that drives cancerogenesis. To elucidate the role of aberrant chromatin features, we mapped DNA methylation, seven histone modifications, nucleosome positions, chromatin accessibility, binding of EBF1 and CTCF, as well as the transcriptome of B cells from CLL patients and healthy donors. A globally increased histone deacetylase activity was detected and half of the genome comprised transcriptionally downregulated partially DNA methylated domains demarcated by CTCF. CLL samples displayed a H3K4me3 redistribution and nucleosome gain at promoters as well as changes of enhancer activity and enhancer linkage to target genes. A DNA binding motif analysis identified transcription factors that gained or lost binding in CLL at sites with aberrant chromatin features. These findings were integrated into a gene regulatory enhancer containing network enriched for B‐cell receptor signaling pathway components. Our study predicts novel molecular links to targets of CLL therapies and provides a valuable resource for further studies on the epigenetic contribution to the disease

The spatio-temporal evolution of multiple myeloma from baseline to relapse-refractory states

Deciphering Multiple Myeloma evolution in the whole bone marrow is key to inform curative strategies. Here, we perform spatial-longitudinal whole-exome sequencing, including 140 samples collected from 24 Multiple Myeloma patients during up to 14 years. Applying imaging-guided sampling we observe three evolutionary patterns, including relapse driven by a single-cell expansion, competing/co-existing sub-clones, and unique sub-clones at distinct locations. While we do not find the unique relapse sub-clone in the baseline focal lesion(s), we show a close phylogenetic relationship between baseline focal lesions and relapse disease, highlighting focal lesions as hotspots of tumor evolution. In patients with ≥3 focal lesions on positron-emission-tomography at diagnosis, relapse is driven by multiple distinct sub-clones, whereas in other patients, a single-cell expansion is typically seen (p < 0.01). Notably, we observe resistant sub-clones that can be hidden over years, suggesting that a prerequisite for curative therapies would be to overcome not only tumor heterogeneity but also dormancy

Implications and Prognostic Impact of Mass Spectrometry in Patients with Newly-Diagnosed Multiple Myeloma

Mass spectrometry (MS) is a promising tool for monitoring monoclonal protein in plasma cell dyscrasias. We included 480 transplant-eligible newly-diagnosed multiple myeloma (MM) patients from the GMMG-MM5 trial (EudraCT No. 2010-019173-16) and performed a retrospective MS analysis at baseline (480 patients) and at the pre-defined, consecutive time points after induction (444 patients), prior to maintenance (305 patients) and after one year of maintenance (227 patients). We found that MS negativity was significantly associated with improved progression-free survival (PFS) even in patients with complete response (CR) at all investigated follow-up time points. The prognostic impact was independent of established risk factors, such as the revised International Staging System. Combining MS and baseline cytogenetics improved the prediction of outcome: MS-positive patients with high-risk cytogenetics had a dismal PFS of 1.9 years (95% confidence interval [CI]: 1.6–2.3 years) from the start of maintenance. Testing the value of sequential MS prior to and after one year of maintenance, patients converting from MS positivity to negativity had an excellent PFS (median not reached) while patients converting from MS negativity to positivity progressed early (median 0.6 years, 95% CI: 0.3-not reached). Among patients with sustained MS positivity, the baseline high-risk cytogenetic status had a significant impact and defined a group with poor PFS. Combining minimal residual disease (MRD) in the bone marrow and MS allowed the identification of double negative patients with a favorable PFS (median 3.33 years, 95% CI: 3.08-not reached) and no overall survival events. Our study provides strong evidence that MS is superior to conventional response monitoring, highlighting the potential of MS to become a new standard. Our data indicate that MS should be performed sequentially and combined with baseline disease features and MRD to improve its clinical value. Clinical Trials Register: EudraCT No. 2010-019173-1

Sequence diversity of kappa light chains from patients with AL amyloidosis and multiple myeloma

AL amyloidosis (AL) results from the misfolding of immunoglobulin light chains (IG LCs). Aim of this study was to comprehensively analyse kappa LC sequences from AL patients in comparison with multiple myeloma (MM). We analysed IGKV/IGKJ usage and associated organ tropism and IGKV1/D-33 in terms of mutational analysis and theoretical biochemical properties. cDNA and bulk RNA sequencing of the LCs of AL and MM patients. We studied 41 AL and 83 MM patients showing that IGKV1 was most expressed among kappa AL and MM, with higher frequency in AL (80% vs. 53%, p = .002). IGKV3 was underrepresented in AL (10% vs. 30%, p = .014). IGKJ2 was more commonly used in AL than in MM (39% vs. 29%). Patients with IGKV1/D-33 were associated with heart involvement (75%, p = .024). IGKV1/D-33-segments of AL had a higher mutation count (AL = 12.0 vs. MM = 10.0). FR3 and CDR3 were most frequently mutated in both, with a median mutation count in FR3 being the highest (AL = 4.0; MM = 3.5) and one mutation hotspot (FR3 (83I)) for IGKV1/D-33/IGKJ2 was associated with cardiac involvement. This study confirmed that germline usage has an influence on AL amyloidosis risk and organ involvement.</p

Genomic Classification and Individualized Prognosis in Multiple Myeloma

PURPOSE Outcomes for patients with newly diagnosed multiple myeloma (NDMM) are heterogenous, with overall survival (OS) ranging from months to over 10 years. METHODS To decipher and predict the molecular and clinical heterogeneity of NDMM, we assembled a series of 1,933 patients with available clinical, genomic, and therapeutic data. RESULTS Leveraging a comprehensive catalog of genomic drivers, we identified 12 groups, expanding on previous gene expression–based molecular classifications. To build a model predicting individualized risk in NDMM (IRMMa), we integrated clinical, genomic, and treatment variables. To correct for time-dependent variables, including high-dose melphalan followed by autologous stem-cell transplantation (HDM-ASCT), and maintenance therapy, a multi-state model was designed. The IRMMa model accuracy was significantly higher than all comparator prognostic models, with a c-index for OS of 0.726, compared with International Staging System (ISS; 0.61), revised-ISS (0.572), and R2-ISS (0.625). Integral to model accuracy was 20 genomic features, including 1q21 gain/amp, del 1p, TP53 loss, NSD2 translocations, APOBEC mutational signatures, and copy-number signatures (reflecting the complex structural variant chromothripsis). IRMMa accuracy and superiority compared with other prognostic models were validated on 256 patients enrolled in the GMMG-HD6 (ClinicalTrials.gov identifier: NCT02495922 ) clinical trial. Individualized patient risks were significantly affected across the 12 genomic groups by different treatment strategies (ie, treatment variance), which was used to identify patients for whom HDM-ASCT is particularly effective versus patients for whom the impact is limited. CONCLUSION Integrating clinical, demographic, genomic, and therapeutic data, to our knowledge, we have developed the first individualized risk-prediction model enabling personally tailored therapeutic decisions for patients with NDMM