Pituitary hCG production and cerebral tuberculosis mimicking disease progression during chemotherapy for an advanced ovarian germ cell tumour

<p>Abstract</p> <p>Background</p> <p>Ovarian germ cell tumours (OGCT) are rare but are usually curable with chemotherapy, even when presenting with advanced disease. The majority of OGCT produce the tumour markers, hCG and/or AFP which can be helpful in the diagnosis and monitoring the response to treatment.</p> <p>Case Presentation</p> <p>In this case of a 36 year old woman, the elevated hCG level at presentation was helpful in making a clinical diagnosis of OGCT in a patient too unwell to permit a tissue diagnosis.</p> <p>Cisplatin based combination chemotherapy produced an initial normalisation of the hCG level, but later in treatment the patient developed new cerebral lesions and a rising serum hCG suggestive of disease progression.</p> <p>Further investigations suggested that the CNS lesions were cerebral TB and that the low levels of hCG elevations was likely to be pituitary in origin. Chemotherapy treatment was continued along with anti-tuberculous therapy and 24 months after successful completion of therapy the patient remains disease free.</p> <p>Conclusions</p> <p>In the treatment of cancer patients it may be helpful to consider the potential non-malignant causes of new CNS lesions and that low hCG elevations may result from physiology rather than pathology in selected cases.</p

An <i>In Vivo</i> 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

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

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/β-catenin, mitogen-activated protein kinase, and TGF-β 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

Differential clonal evolution in oesophageal cancers in response to neo-adjuvant chemotherapy

How chemotherapy affects carcinoma genomes is largely unknown. Here we report whole-exome and deep sequencing of 30 paired oesophageal adenocarcinomas sampled before and after neo-adjuvant chemotherapy. Most, but not all, good responders pass through genetic bottlenecks, a feature associated with higher mutation burden pre-treatment. Some poor responders pass through bottlenecks, but re-grow by the time of surgical resection, suggesting a missed therapeutic opportunity. Cancers often show major changes in driver mutation presence or frequency after treatment, owing to outgrowth persistence or loss of sub-clones, copy number changes, polyclonality and/or spatial genetic heterogeneity. Post-therapy mutation spectrum shifts are also common, particularly C&gt;A and TT&gt;CT changes in good responders or bottleneckers. Post-treatment samples may also acquire mutations in known cancer driver genes (for example, SF3B1, TAF1 and CCND2) that are absent from the paired pre-treatment sample. Neo-adjuvant chemotherapy can rapidly and profoundly affect the oesophageal adenocarcinoma genome. Monitoring molecular changes during treatment may be clinically useful

Neighbours of cancer-related proteins have key influence on pathogenesis and could increase the drug target space for anticancer therapies

Even targeted chemotherapies against solid cancers show a moderate success increasing the need to novel targeting strategies. To address this problem, we designed a systems-level approach investigating the neighbourhood of mutated or differentially expressed cancer-related proteins in four major solid cancers (colon, breast, liver and lung). Using signalling and protein–protein interaction network resources integrated with mutational and expression datasets, we analysed the properties of the direct and indirect interactors (first and second neighbours) of cancer-related proteins, not found previously related to the given cancer type. We found that first neighbours have at least as high degree, betweenness centrality and clustering coefficient as cancer-related proteins themselves, indicating a previously unknown central network position. We identified a complementary strategy for mutated and differentially expressed proteins, where the affect of differentially expressed proteins having smaller network centrality is compensated with high centrality first neighbours. These first neighbours can be considered as key, so far hidden, components in cancer rewiring, with similar importance as mutated proteins. These observations strikingly suggest targeting first neighbours as a novel strategy for disrupting cancer-specific networks. Remarkably, our survey revealed 223 marketed drugs already targeting first neighbour proteins but applied mostly outside oncology, providing a potential list for drug repurposing against solid cancers. For the very central first neighbours, whose direct targeting would cause several side effects, we suggest a cancer-mimicking strategy by targeting their interactors (second neighbours of cancer-related proteins, having a central protein affecting position, similarly to the cancer-related proteins). Hence, we propose to include first neighbours to network medicine based approaches for (but not limited to) anticancer therapies

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