Insights for precision oncology from the integration of genomic and clinical data of 13,880 tumors from the 100,000 Genomes Cancer Programme.

The Cancer Programme of the 100,000 Genomes Project was an initiative to provide whole-genome sequencing (WGS) for patients with cancer, evaluating opportunities for precision cancer care within the UK National Healthcare System (NHS). Genomics England, alongside NHS England, analyzed WGS data from 13,880 solid tumors spanning 33 cancer types, integrating genomic data with real-world treatment and outcome data, within a secure Research Environment. Incidence of somatic mutations in genes recommended for standard-of-care testing varied across cancer types. For instance, in glioblastoma multiforme, small variants were present in 94% of cases and copy number aberrations in at least one gene in 58% of cases, while sarcoma demonstrated the highest occurrence of actionable structural variants (13%). Homologous recombination deficiency was identified in 40% of high-grade serous ovarian cancer cases with 30% linked to pathogenic germline variants, highlighting the value of combined somatic and germline analysis. The linkage of WGS and longitudinal life course clinical data allowed the assessment of treatment outcomes for patients stratified according to pangenomic markers. Our findings demonstrate the utility of linking genomic and real-world clinical data to enable survival analysis to identify cancer genes that affect prognosis and advance our understanding of how cancer genomics impacts patient outcomes.

Genetic and immune landscape evolution in MMR-deficient colorectal cancer.

Mismatch repair-deficient (MMRd) colorectal cancers (CRCs) have high mutation burdens, which make these tumours immunogenic and many respond to immune checkpoint inhibitors. The MMRd hypermutator phenotype may also promote intratumour heterogeneity (ITH) and cancer evolution. We applied multiregion sequencing and CD8 and programmed death ligand 1 (PD-L1) immunostaining to systematically investigate ITH and how genetic and immune landscapes coevolve. All cases had high truncal mutation burdens. Despite pervasive ITH, driver aberrations showed a clear hierarchy. Those in WNT/ß-catenin, mitogen-activated protein kinase, and TGF-ß receptor family genes were almost always truncal. Immune evasion (IE) drivers, such as inactivation of genes involved in antigen presentation or IFN-γ signalling, were predominantly subclonal and showed parallel evolution. These IE drivers have been implicated in immune checkpoint inhibitor resistance or sensitivity. Clonality assessments are therefore important for the development of predictive immunotherapy biomarkers in MMRd CRCs. Phylogenetic analysis identified three distinct patterns of IE driver evolution: pan-tumour evolution, subclonal evolution, and evolutionary stasis. These, but neither mutation burdens nor heterogeneity metrics, significantly correlated with T-cell densities, which were used as a surrogate marker of tumour immunogenicity. Furthermore, this revealed that genetic and T-cell infiltrates coevolve in MMRd CRCs. Low T-cell densities in the subgroup without any known IE drivers may indicate an, as yet unknown, IE mechanism. PD-L1 was expressed in the tumour microenvironment in most samples and correlated with T-cell densities. However, PD-L1 expression in cancer cells was independent of T-cell densities but strongly associated with loss of the intestinal homeobox transcription factor CDX2. This explains infrequent PD-L1 expression by cancer cells and may contribute to a higher recurrence risk of MMRd CRCs with impaired CDX2 expression. © 2023 The Authors. The Journal of Pathology published by John Wiley & Sons Ltd on behalf of The Pathological Society of Great Britain and Ireland.

COVID-19 prevalence and mortality in patients with cancer and the effect of primary tumour subtype and patient demographics: a prospective cohort study.

BACKGROUND: Patients with cancer are purported to have poor COVID-19 outcomes. However, cancer is a heterogeneous group of diseases, encompassing a spectrum of tumour subtypes. The aim of this study was to investigate COVID-19 risk according to tumour subtype and patient demographics in patients with cancer in the UK. METHODS: We compared adult patients with cancer enrolled in the UK Coronavirus Cancer Monitoring Project (UKCCMP) cohort between March 18 and May 8, 2020, with a parallel non-COVID-19 UK cancer control population from the UK Office for National Statistics (2017 data). The primary outcome of the study was the effect of primary tumour subtype, age, and sex and on severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) prevalence and the case-fatality rate during hospital admission. We analysed the effect of tumour subtype and patient demographics (age and sex) on prevalence and mortality from COVID-19 using univariable and multivariable models. FINDINGS: 319 (30·6%) of 1044 patients in the UKCCMP cohort died, 295 (92·5%) of whom had a cause of death recorded as due to COVID-19. The all-cause case-fatality rate in patients with cancer after SARS-CoV-2 infection was significantly associated with increasing age, rising from 0·10 in patients aged 40-49 years to 0·48 in those aged 80 years and older. Patients with haematological malignancies (leukaemia, lymphoma, and myeloma) had a more severe COVID-19 trajectory compared with patients with solid organ tumours (odds ratio [OR] 1·57, 95% CI 1·15-2·15; p<0·0043). Compared with the rest of the UKCCMP cohort, patients with leukaemia showed a significantly increased case-fatality rate (2·25, 1·13-4·57; p=0·023). After correction for age and sex, patients with haematological malignancies who had recent chemotherapy had an increased risk of death during COVID-19-associated hospital admission (OR 2·09, 95% CI 1·09-4·08; p=0·028). INTERPRETATION: Patients with cancer with different tumour types have differing susceptibility to SARS-CoV-2 infection and COVID-19 phenotypes. We generated individualised risk tables for patients with cancer, considering age, sex, and tumour subtype. Our results could be useful to assist physicians in informed risk-benefit discussions to explain COVID-19 risk and enable an evidenced-based approach to national social isolation policies. FUNDING: University of Birmingham and University of Oxford.

COVID-19 mortality in patients with cancer on chemotherapy or other anticancer treatments: a prospective cohort study.

BACKGROUND: Individuals with cancer, particularly those who are receiving systemic anticancer treatments, have been postulated to be at increased risk of mortality from COVID-19. This conjecture has considerable effect on the treatment of patients with cancer and data from large, multicentre studies to support this assumption are scarce because of the contingencies of the pandemic. We aimed to describe the clinical and demographic characteristics and COVID-19 outcomes in patients with cancer. METHODS: In this prospective observational study, all patients with active cancer and presenting to our network of cancer centres were eligible for enrolment into the UK Coronavirus Cancer Monitoring Project (UKCCMP). The UKCCMP is the first COVID-19 clinical registry that enables near real-time reports to frontline doctors about the effects of COVID-19 on patients with cancer. Eligible patients tested positive for severe acute respiratory syndrome coronavirus 2 on RT-PCR assay from a nose or throat swab. We excluded patients with a radiological or clinical diagnosis of COVID-19, without a positive RT-PCR test. The primary endpoint was all-cause mortality, or discharge from hospital, as assessed by the reporting sites during the patient hospital admission. FINDINGS: From March 18, to April 26, 2020, we analysed 800 patients with a diagnosis of cancer and symptomatic COVID-19. 412 (52%) patients had a mild COVID-19 disease course. 226 (28%) patients died and risk of death was significantly associated with advancing patient age (odds ratio 9·42 [95% CI 6·56-10·02]; p<0·0001), being male (1·67 [1·19-2·34]; p=0·003), and the presence of other comorbidities such as hypertension (1·95 [1·36-2·80]; p<0·001) and cardiovascular disease (2·32 [1·47-3·64]). 281 (35%) patients had received cytotoxic chemotherapy within 4 weeks before testing positive for COVID-19. After adjusting for age, gender, and comorbidities, chemotherapy in the past 4 weeks had no significant effect on mortality from COVID-19 disease, when compared with patients with cancer who had not received recent chemotherapy (1·18 [0·81-1·72]; p=0·380). We found no significant effect on mortality for patients with immunotherapy, hormonal therapy, targeted therapy, radiotherapy use within the past 4 weeks. INTERPRETATION: Mortality from COVID-19 in cancer patients appears to be principally driven by age, gender, and comorbidities. We are not able to identify evidence that cancer patients on cytotoxic chemotherapy or other anticancer treatment are at an increased risk of mortality from COVID-19 disease compared with those not on active treatment. FUNDING: University of Birmingham, University of Oxford.

An In Vivo Functional Screen Identifies JNK Signaling As a Modulator of Chemotherapeutic Response in Breast Cancer.

Chemotherapy remains the mainstay of treatment for advanced breast cancer; however, resistance is an inevitable event for the majority of patients with metastatic disease. Moreover, there is little information available to guide stratification of first-line chemotherapy, crucial given the common development of multidrug resistance. Here, we describe an in vivo screen to interrogate the response to anthracycline-based chemotherapy in a syngeneic metastatic breast cancer model and identify JNK signaling as a key modulator of chemotherapy response. Combining in vitro and in vivo functional analyses, we demonstrate that JNK inhibition both promotes tumor cell cytostasis and blocks activation of the proapoptotic protein Bax, thereby antagonizing chemotherapy-mediated cytotoxicity. To investigate the clinical relevance of this dual role of JNK signaling, we developed a proliferation-independent JNK activity signature and demonstrate high JNK activity to be enriched in triple-negative and basal-like breast cancer subtypes. Consistent with the dual role of JNK signaling in vitro, high-level JNK pathway activation in triple-negative breast cancers is associated both with poor patient outcome in the absence of chemotherapy treatment and, in neoadjuvant clinical studies, is predictive of enhanced chemotherapy response. These data highlight the potential of monitoring JNK activity as early biomarker of response to chemotherapy and emphasize the importance of rational treatment regimes, particularly when combining cytostatic and chemotherapeutic agents. Mol Cancer Ther; 16(9); 1967-78. ©2017 AACR.

Clonal neoantigens elicit T cell immunoreactivity and sensitivity to immune checkpoint blockade.

As tumors grow, they acquire mutations, some of which create neoantigens that influence the response of patients to immune checkpoint inhibitors. We explored the impact of neoantigen intratumor heterogeneity (ITH) on antitumor immunity. Through integrated analysis of ITH and neoantigen burden, we demonstrate a relationship between clonal neoantigen burden and overall survival in primary lung adenocarcinomas. CD8(+)tumor-infiltrating lymphocytes reactive to clonal neoantigens were identified in early-stage non-small cell lung cancer and expressed high levels of PD-1. Sensitivity to PD-1 and CTLA-4 blockade in patients with advanced NSCLC and melanoma was enhanced in tumors enriched for clonal neoantigens. T cells recognizing clonal neoantigens were detectable in patients with durable clinical benefit. Cytotoxic chemotherapy-induced subclonal neoantigens, contributing to an increased mutational load, were enriched in certain poor responders. These data suggest that neoantigen heterogeneity may influence immune surveillance and support therapeutic developments targeting clonal neoantigens.

Tracking the genomic evolution of esophageal adenocarcinoma through neoadjuvant chemotherapy.

UNLABELLED: Esophageal adenocarcinomas are associated with a dismal prognosis. Deciphering the evolutionary history of this disease may shed light on therapeutically tractable targets and reveal dynamic mutational processes during the disease course and following neoadjuvant chemotherapy (NAC). We exome sequenced 40 tumor regions from 8 patients with operable esophageal adenocarcinomas, before and after platinum-containing NAC. This revealed the evolutionary genomic landscape of esophageal adenocarcinomas with the presence of heterogeneous driver mutations, parallel evolution, early genome-doubling events, and an association between high intratumor heterogeneity and poor response to NAC. Multiregion sequencing demonstrated a significant reduction in thymine to guanine mutations within a CpTpT context when comparing early and late mutational processes and the presence of a platinum signature with enrichment of cytosine to adenine mutations within a CpC context following NAC. Esophageal adenocarcinomas are characterized by early chromosomal instability leading to amplifications containing targetable oncogenes persisting through chemotherapy, providing a rationale for future therapeutic approaches. SIGNIFICANCE: This work illustrates dynamic mutational processes occurring during esophageal adenocarcinoma evolution and following selective pressures of platinum exposure, emphasizing the iatrogenic impact of therapy on cancer evolution. Identification of amplifications encoding targetable oncogenes maintained through NAC suggests the presence of stable vulnerabilities, unimpeded by cytotoxics, suitable for therapeutic intervention.

Spatial and temporal diversity in genomic instability processes defines lung cancer evolution.

Spatial and temporal dissection of the genomic changes occurring during the evolution of human non-small cell lung cancer (NSCLC) may help elucidate the basis for its dismal prognosis. We sequenced 25 spatially distinct regions from seven operable NSCLCs and found evidence of branched evolution, with driver mutations arising before and after subclonal diversification. There was pronounced intratumor heterogeneity in copy number alterations, translocations, and mutations associated with APOBEC cytidine deaminase activity. Despite maintained carcinogen exposure, tumors from smokers showed a relative decrease in smoking-related mutations over time, accompanied by an increase in APOBEC-associated mutations. In tumors from former smokers, genome-doubling occurred within a smoking-signature context before subclonal diversification, which suggested that a long period of tumor latency had preceded clinical detection. The regionally separated driver mutations, coupled with the relentless and heterogeneous nature of the genome instability processes, are likely to confound treatment success in NSCLC.

Tracking genomic cancer evolution for precision medicine: the lung TRACERx study.

The importance of intratumour genetic and functional heterogeneity is increasingly recognised as a driver of cancer progression and survival outcome. Understanding how tumour clonal heterogeneity impacts upon therapeutic outcome, however, is still an area of unmet clinical and scientific need. TRACERx (TRAcking non-small cell lung Cancer Evolution through therapy [Rx]), a prospective study of patients with primary non-small cell lung cancer (NSCLC), aims to define the evolutionary trajectories of lung cancer in both space and time through multiregion and longitudinal tumour sampling and genetic analysis. By following cancers from diagnosis to relapse, tracking the evolutionary trajectories of tumours in relation to therapeutic interventions, and determining the impact of clonal heterogeneity on clinical outcomes, TRACERx may help to identify novel therapeutic targets for NSCLC and may also serve as a model applicable to other cancer types.

An in vivo functional screen identifies ST6GalNAc2 sialyltransferase as a breast cancer metastasis suppressor.

To interrogate the complex mechanisms involved in the later stages of cancer metastasis, we designed a functional in vivo RNA interference (RNAi) screen combined with next-generation sequencing. Using this approach, we identified the sialyltransferase ST6GalNAc2 as a novel breast cancer metastasis suppressor. Mechanistically, ST6GalNAc2 silencing alters the profile of O-glycans on the tumor cell surface, facilitating binding of the soluble lectin galectin-3. This then enhances tumor cell retention and emboli formation at metastatic sites leading to increased metastatic burden, events that can be completely blocked by galectin-3 inhibition. Critically, elevated ST6GALNAC2, but not galectin-3, expression in estrogen receptor-negative breast cancers significantly correlates with reduced frequency of metastatic events and improved survival. These data demonstrate that the prometastatic role of galectin-3 is regulated by its ability to bind to the tumor cell surface and highlight the potential of monitoring ST6GalNAc2 expression to stratify patients with breast cancer for treatment with galectin-3 inhibitors.

Adapting clinical paradigms to the challenges of cancer clonal evolution.

Emerging evidence suggests that cancer branched evolution may affect biomarker validation, clinical outcome, and emergence of drug resistance. The changing spatial and temporal nature of cancer subclonal architecture during the disease course suggests the need for longitudinal prospective studies of cancer evolution and robust and clinically implementable pathologic definitions of intratumor heterogeneity, genetic diversity, and chromosomal instability. Furthermore, subclonal heterogeneous events in tumors may evade detection through conventional biomarker strategies and influence clinical outcome. Minimally invasive methods for the study of cancer evolution and new approaches to clinical study design, incorporating understanding of the dynamics of tumor clonal architectures through treatment and during acquisition of drug resistance, have been suggested as important areas for development. Coordinated efforts will be required by the scientific and clinical trial communities to adapt to the challenges of detecting infrequently occurring somatic events that may influence clinical outcome and to understand the dynamics of cancer evolution and the waxing and waning of tumor subclones over time in advanced metastatic epithelial malignancies.

Whole genome in vivo RNAi screening identifies the leukemia inhibitory factor receptor as a novel breast tumor suppressor.

Cancer is caused by mutations in oncogenes and tumor suppressor genes, resulting in the deregulation of processes fundamental to the normal behavior of cells. The identification and characterization of oncogenes and tumor suppressors has led to new treatment strategies that have significantly improved cancer outcome. The advent of next generation sequencing has allowed the elucidation of the fine structure of cancer genomes, however, the identification of pathogenic changes is complicated by the inherent genomic instability of cancer cells. Therefore, functional approaches for the identification of novel genes involved in the initiation and development of tumors are critical. Here we report the first whole human genome in vivo RNA interference screen to identify functionally important tumor suppressor genes. Using our novel approach, we identify previously validated tumor suppressor genes including TP53 and MNT, as well as several novel candidate tumor suppressor genes including leukemia inhibitory factor receptor (LIFR). We show that LIFR is a key novel tumor suppressor, whose deregulation may drive the transformation of a significant proportion of human breast cancers. These results demonstrate the power of genome wide in vivo RNAi screens as a method for identifying novel genes regulating tumorigenesis.

High-throughput RNA interference screening using pooled shRNA libraries and next generation sequencing.

RNA interference (RNAi) screening is a state-of-the-art technology that enables the dissection of biological processes and disease-related phenotypes. The commercial availability of genome-wide, short hairpin RNA (shRNA) libraries has fueled interest in this area but the generation and analysis of these complex data remain a challenge. Here, we describe complete experimental protocols and novel open source computational methodologies, shALIGN and shRNAseq, that allow RNAi screens to be rapidly deconvoluted using next generation sequencing. Our computational pipeline offers efficient screen analysis and the flexibility and scalability to quickly incorporate future developments in shRNA library technology.

Malignant ovarian germ cell tumors: identification of novel prognostic markers and long-term outcome after multimodality treatment.

PURPOSE: Malignant ovarian germ cell tumors are rare and knowledge about prognostic parameters currently is limited. This study was undertaken to evaluate long-term outcome of patients with malignant ovarian germ cell tumors (MOGCTs) after chemotherapy and to assess prognostic parameters. PATIENTS AND METHODS: A total of 113 patients with stage IC to IV MOGCTs were included into this retrospective study. Patients were treated at two large regional cancer centers between 1977 and 2003. RESULTS: Ten-year recurrence-free and overall survival rates were 82% and 81%, respectively. A total of 20 patients experienced relapse, all within the first 8 years. Outcome after relapse was poor, with only 10% of patients achieving long-term survival. Univariate and multivariate analyses demonstrated that initial stage of disease (relative risk [RR], 5.96; 95% CI, 3.47 to 10.22; P = .03) and elevation of serum markers beta-human chorionic gonadotropin and alpha-fetoprotein (RR, 3.90; 95% CI, 1.40 to 10.9; P = .009) were significant predictors of overall survival, whereas age at diagnosis was of no prognostic value. CONCLUSION: This is the first study to identify stage and tumor markers as prognostic parameters for patients with MOGCTs. This might help to select patients for risk-adapted treatment. There is need for improvement of therapeutic strategies after relapse.