Independent transcriptional patterns reveal biological processes associated with disease-free survival in early colorectal cancer.

BACKGROUND: Bulk transcriptional profiles of early colorectal cancer (CRC) can fail to detect biological processes associated with disease-free survival (DFS) if the transcriptional patterns are subtle and/or obscured by other processes' patterns. Consensus-independent component analysis (c-ICA) can dissect such transcriptomes into statistically independent transcriptional components (TCs), capturing both pronounced and subtle biological processes. METHODS: In this study we (1) integrated transcriptomes (n = 4228) from multiple early CRC studies, (2) performed c-ICA to define the TC landscape within this integrated data set, 3) determined the biological processes captured by these TCs, (4) performed Cox regression to identify DFS-associated TCs, (5) performed random survival forest (RSF) analyses with activity of DFS-associated TCs as classifiers to identify subgroups of patients, and 6) performed a sensitivity analysis to determine the robustness of our results RESULTS: We identify 191 TCs, 43 of which are associated with DFS, revealing transcriptional diversity among DFS-associated biological processes. A prominent example is the epithelial-mesenchymal transition (EMT), for which we identify an association with nine independent DFS-associated TCs, each with coordinated upregulation or downregulation of various sets of genes. CONCLUSIONS: This finding indicates that early CRC may have nine distinct routes to achieve EMT, each requiring a specific peri-operative treatment strategy. Finally, we stratify patients into DFS patient subgroups with distinct transcriptional patterns associated with stage 2 and stage 3 CRC.

While treatments for patients with colorectal cancer have improved, many patients (around 30-50%) have cancers that will eventually relapse and these patients will die due to their disease. Researchers have been studying the genes involved in colorectal cancer to help us understand why some cancers might relapse. However, current methods to do this may miss subtle or hidden patterns in the gene activity related to cancer relapse. To deal with this, we used a special method called consensus-independent component analysis (c-ICA) to dig more deeply into the activity of genes. This helped us to uncover some potential biological processes underpinning colorectal cancer relapse, which ultimately could help researchers to identify better treatments for patients with colorectal cancer.

A Survival Tree of Advanced Melanoma Patients with Brain Metastases Treated with Immune Checkpoint Inhibitors.

The efficacy of immune checkpoint inhibitors (ICIs) in patients with advanced melanoma that develop brain metastases (BM) remains unpredictable. In this study, we aimed to identify prognostic factors in patients with melanoma BM who are treated with ICIs. Data from advanced melanoma patients with BM treated with ICIs in any line between 2013 and 2020 were obtained from the Dutch Melanoma Treatment Registry. Patients were included from the time of the treatment of BM with ICIs. Survival tree analysis was performed with clinicopathological parameters as potential classifiers and overall survival (OS) as the response variable. In total, 1278 patients were included. Most patients were treated with ipilimumab-nivolumab combination therapy (45%). The survival tree analysis resulted in 31 subgroups. The median OS ranged from 2.7 months to 35.7 months. The strongest clinical parameter associated with survival in advanced melanoma patients with BM was the serum lactate dehydrogenase (LDH) level. Patients with elevated LDH levels and symptomatic BM had the worst prognosis. The clinicopathological classifiers identified in this study can contribute to optimizing clinical studies and can aid doctors in giving an indication of the patients' survival based on their baseline and disease characteristics.

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

Joint DNA molecules are natural byproducts of DNA replication and repair. Persistent joint molecules give rise to ultrafine DNA bridges (UFBs) in mitosis, compromising sister chromatid separation. The DNA translocase PICH (ERCC6L) has a central role in UFB resolution. A genome-wide loss-of-function screen is performed to identify the genetic context of PICH dependency. In addition to genes involved in DNA condensation, centromere stability, and DNA-damage repair, we identify FIGNL1-interacting regulator of recombination and mitosis (FIRRM), formerly known as C1orf112. We find that FIRRM interacts with and stabilizes the AAA+ ATPase FIGNL1. Inactivation of either FIRRM or FIGNL1 results in UFB formation, prolonged accumulation of RAD51 at nuclear foci, and impaired replication fork dynamics and consequently impairs genome maintenance. Combined, our data suggest that inactivation of FIRRM and FIGNL1 dysregulates RAD51 dynamics at replication forks, resulting in persistent DNA lesions and a dependency on PICH to preserve cell viability.

MYC promotes immune-suppression in triple-negative breast cancer via inhibition of interferon signaling.

The limited efficacy of immune checkpoint inhibitor treatment in triple-negative breast cancer (TNBC) patients is attributed to sparse or unresponsive tumor-infiltrating lymphocytes, but the mechanisms that lead to a therapy resistant tumor immune microenvironment are incompletely known. Here we show a strong correlation between MYC expression and loss of immune signatures in human TNBC. In mouse models of TNBC proficient or deficient of breast cancer type 1 susceptibility gene (BRCA1), MYC overexpression dramatically decreases lymphocyte infiltration in tumors, along with immune signature remodelling. MYC-mediated suppression of inflammatory signalling induced by BRCA1/2 inactivation is confirmed in human TNBC cell lines. Moreover, MYC overexpression prevents the recruitment and activation of lymphocytes in both human and mouse TNBC co-culture models. Chromatin-immunoprecipitation-sequencing reveals that MYC, together with its co-repressor MIZ1, directly binds promoters of multiple interferon-signalling genes, resulting in their downregulation. MYC overexpression thus counters tumor growth inhibition by a Stimulator of Interferon Genes (STING) agonist via suppressing induction of interferon signalling. Together, our data reveal that MYC suppresses innate immunity and facilitates tumor immune escape, explaining the poor immunogenicity of MYC-overexpressing TNBCs.

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

Oncogene-induced replication stress characterizes many aggressive cancers. Several treatments are being developed that target replication stress, however, identification of tumors with high levels of replication stress remains challenging. We describe a gene expression signature of oncogene-induced replication stress. A panel of triple-negative breast cancer (TNBC) and non-transformed cell lines were engineered to overexpress CDC25A, CCNE1 or MYC, which resulted in slower replication kinetics. RNA sequencing analysis revealed a set of 52 commonly upregulated genes. In parallel, mRNA expression analysis of patient-derived tumor samples (TCGA, n = 10,592) also revealed differential gene expression in tumors with amplification of oncogenes that trigger replication stress (CDC25A, CCNE1, MYC, CCND1, MYB, MOS, KRAS, ERBB2, and E2F1). Upon integration, we identified a six-gene signature of oncogene-induced replication stress (NAT10, DDX27, ZNF48, C8ORF33, MOCS3, and MPP6). Immunohistochemical analysis of NAT10 in breast cancer samples (n = 330) showed strong correlation with expression of phospho-RPA (R = 0.451, p = 1.82 × 10-20) and γH2AX (R = 0.304, p = 2.95 × 10-9). Finally, we applied our oncogene-induced replication stress signature to patient samples from TCGA (n = 8,862) and GEO (n = 13,912) to define the levels of replication stress across 27 tumor subtypes, identifying diffuse large B cell lymphoma, ovarian cancer, TNBC and colorectal carcinoma as cancer subtypes with high levels of oncogene-induced replication stress.

mRNA-1273 COVID-19 vaccination in patients receiving chemotherapy, immunotherapy, or chemoimmunotherapy for solid tumours: a prospective, multicentre, non-inferiority trial.

BACKGROUND: Patients with cancer have an increased risk of complications from SARS-CoV-2 infection. Vaccination to prevent COVID-19 is recommended, but data on the immunogenicity and safety of COVID-19 vaccines for patients with solid tumours receiving systemic cancer treatment are scarce. Therefore, we aimed to assess the impact of immunotherapy, chemotherapy, and chemoimmunotherapy on the immunogenicity and safety of the mRNA-1273 (Moderna Biotech, Madrid, Spain) COVID-19 vaccine as part of the Vaccination Against COVID in Cancer (VOICE) trial. METHODS: This prospective, multicentre, non-inferiority trial was done across three centres in the Netherlands. Individuals aged 18 years or older with a life expectancy of more than 12 months were enrolled into four cohorts: individuals without cancer (cohort A [control cohort]), and patients with solid tumours, regardless of stage and histology, treated with immunotherapy (cohort B), chemotherapy (cohort C), or chemoimmunotherapy (cohort D). Participants received two mRNA-1273 vaccinations of 100 µg in 0·5 mL intramuscularly, 28 days apart. The primary endpoint, analysed per protocol (excluding patients with a positive baseline sample [>10 binding antibody units (BAU)/mL], indicating previous SARS-CoV-2 infection), was defined as the SARS-CoV-2 spike S1-specific IgG serum antibody response (ie, SARS-CoV-2-binding antibody concentration of >10 BAU/mL) 28 days after the second vaccination. For the primary endpoint analysis, a non-inferiority design with a margin of 10% was used. We also assessed adverse events in all patients who received at least one vaccination, and recorded solicited adverse events in participants who received at least one vaccination but excluding those who already had seroconversion (>10 BAU/mL) at baseline. This study is ongoing and is registered with ClinicalTrials.gov, NCT04715438. FINDINGS: Between Feb 17 and March 12, 2021, 791 participants were enrolled and followed up for a median of 122 days (IQR 118 to 128). A SARS-CoV-2-binding antibody response was found in 240 (100%; 95% CI 98 to 100) of 240 evaluable participants in cohort A, 130 (99%; 96 to >99) of 131 evaluable patients in cohort B, 223 (97%; 94 to 99) of 229 evaluable patients in cohort C, and 143 (100%; 97 to 100) of 143 evaluable patients in cohort D. The SARS-CoV-2-binding antibody response in each patient cohort was non-inferior compared with cohort A. No new safety signals were observed. Grade 3 or worse serious adverse events occurred in no participants in cohort A, three (2%) of 137 patients in cohort B, six (2%) of 244 patients in cohort C, and one (1%) of 163 patients in cohort D, with four events (two of fever, and one each of diarrhoea and febrile neutropenia) potentially related to the vaccination. There were no vaccine-related deaths. INTERPRETATION: Most patients with cancer develop, while receiving chemotherapy, immunotherapy, or both for a solid tumour, an adequate antibody response to vaccination with the mRNA-1273 COVID-19 vaccine. The vaccine is also safe in these patients. The minority of patients with an inadequate response after two vaccinations might benefit from a third vaccination. FUNDING: ZonMw, The Netherlands Organisation for Health Research and Development.

Improving gene function predictions using independent transcriptional components.

The interpretation of high throughput sequencing data is limited by our incomplete functional understanding of coding and non-coding transcripts. Reliably predicting the function of such transcripts can overcome this limitation. Here we report the use of a consensus independent component analysis and guilt-by-association approach to predict over 23,000 functional groups comprised of over 55,000 coding and non-coding transcripts using publicly available transcriptomic profiles. We show that, compared to using Principal Component Analysis, Independent Component Analysis-derived transcriptional components enable more confident functionality predictions, improve predictions when new members are added to the gene sets, and are less affected by gene multi-functionality. Predictions generated using human or mouse transcriptomic data are made available for exploration in a publicly available web portal.

Overexpression of Cyclin E1 or Cdc25A leads to replication stress, mitotic aberrancies, and increased sensitivity to replication checkpoint inhibitors.

Oncogene-induced replication stress, for instance as a result of Cyclin E1 overexpression, causes genomic instability and has been linked to tumorigenesis. To survive high levels of replication stress, tumors depend on pathways to deal with these DNA lesions, which represent a therapeutically actionable vulnerability. We aimed to uncover the consequences of Cyclin E1 or Cdc25A overexpression on replication kinetics, mitotic progression, and the sensitivity to inhibitors of the WEE1 and ATR replication checkpoint kinases. We modeled oncogene-induced replication stress using inducible expression of Cyclin E1 or Cdc25A in non-transformed RPE-1 cells, either in a TP53 wild-type or TP53-mutant background. DNA fiber analysis showed Cyclin E1 or Cdc25A overexpression to slow replication speed. The resulting replication-derived DNA lesions were transmitted into mitosis causing chromosome segregation defects. Single cell sequencing revealed that replication stress and mitotic defects upon Cyclin E1 or Cdc25A overexpression resulted in genomic instability. ATR or WEE1 inhibition exacerbated the mitotic aberrancies induced by Cyclin E1 or Cdc25A overexpression, and caused cytotoxicity. Both these phenotypes were exacerbated upon p53 inactivation. Conversely, downregulation of Cyclin E1 rescued both replication kinetics, as well as sensitivity to ATR and WEE1 inhibitors. Taken together, Cyclin E1 or Cdc25A-induced replication stress leads to mitotic segregation defects and genomic instability. These mitotic defects are exacerbated by inhibition of ATR or WEE1 and therefore point to mitotic catastrophe as an underlying mechanism. Importantly, our data suggest that Cyclin E1 overexpression can be used to select patients for treatment with replication checkpoint inhibitors.

Transcriptional effects of copy number alterations in a large set of human cancers.

Copy number alterations (CNAs) can promote tumor progression by altering gene expression levels. Due to transcriptional adaptive mechanisms, however, CNAs do not always translate proportionally into altered expression levels. By reanalyzing >34,000 gene expression profiles, we reveal the degree of transcriptional adaptation to CNAs in a genome-wide fashion, which strongly associate with distinct biological processes. We then develop a platform-independent method-transcriptional adaptation to CNA profiling (TACNA profiling)-that extracts the transcriptional effects of CNAs from gene expression profiles without requiring paired CNA profiles. By applying TACNA profiling to >28,000 patient-derived tumor samples we define the landscape of transcriptional effects of CNAs. The utility of this landscape is demonstrated by the identification of four genes that are predicted to be involved in tumor immune evasion when transcriptionally affected by CNAs. In conclusion, we provide a novel tool to gain insight into how CNAs drive tumor behavior via altered expression levels.

Validation and update of a lymph node metastasis prediction model for breast cancer.

PURPOSE: This study aimed to validate and update a model for predicting the risk of axillary lymph node (ALN) metastasis for assisting clinical decision-making. METHODS: We included breast cancer patients diagnosed at six Dutch hospitals between 2011 and 2015 to validate the original model which includes six variables: clinical tumor size, tumor grade, estrogen receptor status, lymph node longest axis, cortical thickness and hilum status as detected by ultrasonography. Subsequently, we updated the original model using generalized linear model (GLM) tree analysis and by adjusting its intercept and slope. The area under the receiver operator characteristic curve (AUC) and calibration curve were used to assess the original and updated models. Clinical usefulness of the model was evaluated by false-negative rates (FNRs) at different cut-off points for the predictive probability. RESULTS: Data from 1416 patients were analyzed. The AUC for the original model was 0.774. Patients were classified into four risk groups by GLM analysis, for which four updated models were created. The AUC for the updated models was 0.812. The calibration curves showed that the updated model predictions were better in agreement with actual observations than the original model predictions. FNRs of the updated models were lower than the preset 10% at all cut-off points when the predictive probability was less than 12.0%. CONCLUSIONS: The original model showed good performance in the Dutch validation population. The updated models resulted in more accurate ALN metastasis prediction and could be useful preoperative tools in selecting low-risk patients for omission of axillary surgery.