Clusterin expression is upregulated following acute head injury and localizes to astrocytes in old head injury.

There is mounting evidence linking traumatic brain injury (TBI) to neurodegeneration. Clusterin (apolipoprotein J or ApoJ) is a complement inhibitor that appears to have a neuroprotective effect in response to tissue damage and has been reported to be upregulated in Alzheimer's disease. Here we investigated the time course and cellular expression pattern of clusterin in human TBI. Tissue from 32 patients with TBI of varying survival times (from under 30 min to 10 months) was examined using immunohistochemistry for clusterin alongside other markers of neurodegeneration and neuroinflammation. TBI cases were compared to ischemic brain damage, Alzheimer's disease and controls. Double immunofluorescence was carried out in order to examine cellular expression. Clusterin was initially expressed in an axonal location less than 30 min following TBI and increased in intensity and the frequency of deposits with increasing survival time up to 24 h, after which it appeared to reduce in intensity but was still evident several weeks after injury. Clusterin was first evident in astrocytes after 45 min, being increasingly seen up to 48 h but remaining intense in TBI cases with long survival times. Our results suggest clusterin plays a role in modulating the inflammatory response of acute and chronic TBI and that it is a useful marker for TBI, particularly in cases with short survival times. Its prominent accumulation in astrocytes, alongside a mounting inflammatory response and activation of microglial cells supports a potential role in the neurodegenerative changes that occur as a result of TBI.

SF3B1 hotspot mutations confer sensitivity to PARP inhibition by eliciting a defective replication stress response.

SF3B1 hotspot mutations are associated with a poor prognosis in several tumor types and lead to global disruption of canonical splicing. Through synthetic lethal drug screens, we identify that SF3B1 mutant (SF3B1MUT) cells are selectively sensitive to poly (ADP-ribose) polymerase inhibitors (PARPi), independent of hotspot mutation and tumor site. SF3B1MUT cells display a defective response to PARPi-induced replication stress that occurs via downregulation of the cyclin-dependent kinase 2 interacting protein (CINP), leading to increased replication fork origin firing and loss of phosphorylated CHK1 (pCHK1; S317) induction. This results in subsequent failure to resolve DNA replication intermediates and G2/M cell cycle arrest. These defects are rescued through CINP overexpression, or further targeted by a combination of ataxia-telangiectasia mutated and PARP inhibition. In vivo, PARPi produce profound antitumor effects in multiple SF3B1MUT cancer models and eliminate distant metastases. These data provide the rationale for testing the clinical efficacy of PARPi in a biomarker-driven, homologous recombination proficient, patient population.

Analysis and forecasts for trends of COVID-19 in Pakistan using Bayesian models.

BACKGROUND: COVID-19 is currently on full flow in Pakistan. Given the health facilities in the country, there are serious threats in the upcoming months which could be very testing for all the stakeholders. Therefore, there is a need to analyze and forecast the trends of COVID-19 in Pakistan. METHODS: We have analyzed and forecasted the patterns of this pandemic in the country, for next 30 days, using Bayesian structural time series models. The causal impacts of lifting lockdown have also been investigated using intervention analysis under Bayesian structural time series models. The forecasting accuracy of the proposed models has been compared with frequently used autoregressive integrated moving average models. The validity of the proposed model has been investigated using similar datasets from neighboring countries including Iran and India. RESULTS: We observed the improved forecasting accuracy of Bayesian structural time series models as compared to frequently used autoregressive integrated moving average models. As far as the forecasts are concerned, on August 10, 2020, the country is expected to have 333,308 positive cases with 95% prediction interval [275,034-391,077]. Similarly, the number of deaths in the country is expected to reach 7,187 [5,978-8,390] and recoveries may grow to 279,602 [208,420-295,740]. The lifting of lockdown has caused an absolute increase of 98,768 confirmed cases with 95% interval [85,544-111,018], during the post-lockdown period. The positive aspect of the forecasts is that the number of active cases is expected to decrease to 63,706 [18,614-95,337], on August 10, 2020. This is the time for the concerned authorities to further restrict the active cases so that the recession of the outbreak continues in the next month.

Bayesian Analysis of Cancer Data Using a 4-Component Exponential Mixture Model.

Cancer is among the major public health problems as well as a burden for Pakistan. About 148,000 new patients are diagnosed with cancer each year, and almost 100,000 patients die due to this fatal disease. Lung, breast, liver, cervical, blood/bone marrow, and oral cancers are the most common cancers in Pakistan. Perhaps smoking, physical inactivity, infections, exposure to toxins, and unhealthy diet are the main factors responsible for the spread of cancer. We preferred a novel four-component mixture model under Bayesian estimation to estimate the average number of incidences and death of both genders in different age groups. For this purpose, we considered 28 different kinds of cancers diagnosed in recent years. Data of registered patients all over Pakistan in the year 2012 were taken from GLOBOCAN. All the patients were divided into 4 age groups and also split based on genders to be applied to the proposed mixture model. Bayesian analysis is performed on the data using a four-component exponential mixture model. Estimators for mixture model parameters are derived under Bayesian procedures using three different priors and two loss functions. Simulation study and graphical representation for the estimates are also presented. It is noted from analysis of real data that the Bayes estimates under LINEX loss assuming Jeffreys' prior is more efficient for the no. of incidences in male and female. As far as no. of deaths are concerned again, LINEX loss assuming Jeffreys' prior gives better results for the male population, but for the female population, the best loss function is SELF assuming Jeffreys' prior.

3D Functional Genomics Screens Identify CREBBP as a Targetable Driver in Aggressive Triple-Negative Breast Cancer.

Triple-negative breast cancers (TNBC) are resistant to standard-of-care chemotherapy and lack known targetable driver gene alterations. Identification of novel drivers could aid the discovery of new treatment strategies for this hard-to-treat patient population, yet studies using high-throughput and accurate models to define the functions of driver genes in TNBC to date have been limited. Here, we employed unbiased functional genomics screening of the 200 most frequently mutated genes in breast cancer, using spheroid cultures to model in vivo-like conditions, and identified the histone acetyltransferase CREBBP as a novel tumor suppressor in TNBC. CREBBP protein expression in patient tumor samples was absent in 8% of TNBCs and at a high frequency in other tumors, including squamous lung cancer, where CREBBP-inactivating mutations are common. In TNBC, CREBBP alterations were associated with higher genomic heterogeneity and poorer patient survival and resulted in upregulation and dependency on a FOXM1 proliferative program. Targeting FOXM1-driven proliferation indirectly with clinical CDK4/6 inhibitors (CDK4/6i) selectively impaired growth in spheroids, cell line xenografts, and patient-derived models from multiple tumor types with CREBBP mutations or loss of protein expression. In conclusion, we have identified CREBBP as a novel driver in aggressive TNBC and identified an associated genetic vulnerability in tumor cells with alterations in CREBBP and provide a preclinical rationale for assessing CREBBP alterations as a biomarker of CDK4/6i response in a new patient population. SIGNIFICANCE: This study demonstrates that CREBBP genomic alterations drive aggressive TNBC, lung cancer, and lymphomas and may be selectively treated with clinical CDK4/6 inhibitors.

SOX11 promotes epithelial/mesenchymal hybrid state and alters tropism of invasive breast cancer cells.

SOX11 is an embryonic mammary epithelial marker that is normally silenced prior to birth. High SOX11 levels in breast tumours are significantly associated with distant metastasis and poor outcome in breast cancer patients. Here, we show that SOX11 confers distinct features to ER-negative DCIS.com breast cancer cells, leading to populations enriched with highly plastic hybrid epithelial/mesenchymal cells, which display invasive features and alterations in metastatic tropism when xenografted into mice. We found that SOX11+DCIS tumour cells metastasize to brain and bone at greater frequency and to lungs at lower frequency compared to cells with lower SOX11 levels. High levels of SOX11 leads to the expression of markers associated with mesenchymal state and embryonic cellular phenotypes. Our results suggest that SOX11 may be a potential biomarker for breast tumours with elevated risk of developing metastases and may require more aggressive therapies.

Integrin-Mediated Macrophage Adhesion Promotes Lymphovascular Dissemination in Breast Cancer.

Lymphatic vasculature is crucial for metastasis in triple-negative breast cancer (TNBC); however, cellular and molecular drivers controlling lymphovascular metastasis are poorly understood. We define a macrophage-dependent signaling cascade that facilitates metastasis through lymphovascular remodeling. TNBC cells instigate mRNA changes in macrophages, resulting in ß4 integrin-dependent adhesion to the lymphovasculature. ß4 integrin retains macrophages proximal to lymphatic endothelial cells (LECs), where release of TGF-ß1 drives LEC contraction via RhoA activation. Macrophages promote gross architectural changes to lymphovasculature by increasing dilation, hyperpermeability, and disorganization. TGF-ß1 drives ß4 integrin clustering at the macrophage plasma membrane, further promoting macrophage adhesion and demonstrating the dual functionality of TGF-ß1 signaling in this context. ß4 integrin-expressing macrophages were identified in human breast tumors, and a combination of vascular-remodeling macrophage gene signature and TGF-ß signaling scores correlates with metastasis. We postulate that future clinical strategies for patients with TNBC should target crosstalk between ß4 integrin and TGF-ß1.

Integrated genomics and functional validation identifies malignant cell specific dependencies in triple negative breast cancer.

Triple negative breast cancers (TNBCs) lack recurrent targetable driver mutations but demonstrate frequent copy number aberrations (CNAs). Here, we describe an integrative genomic and RNAi-based approach that identifies and validates gene addictions in TNBCs. CNAs and gene expression alterations are integrated and genes scored for pre-specified target features revealing 130 candidate genes. We test functional dependence on each of these genes using RNAi in breast cancer and non-malignant cells, validating malignant cell selective dependence upon 37 of 130 genes. Further analysis reveals a cluster of 13 TNBC addiction genes frequently co-upregulated that includes genes regulating cell cycle checkpoints, DNA damage response, and malignant cell selective mitotic genes. We validate the mechanism of addiction to a potential drug target: the mitotic kinesin family member C1 (KIFC1/HSET), essential for successful bipolar division of centrosome-amplified malignant cells and develop a potential selection biomarker to identify patients with tumors exhibiting centrosome amplification.

RORγt+ Innate Lymphoid Cells Promote Lymph Node Metastasis of Breast Cancers.

Cancer cells tend to metastasize first to tumor-draining lymph nodes, but the mechanisms mediating cancer cell invasion into the lymphatic vasculature remain little understood. Here, we show that in the human breast tumor microenvironment (TME), the presence of increased numbers of RORγt+ group 3 innate lymphoid cells (ILC3) correlates with an increased likelihood of lymph node metastasis. In a preclinical mouse model of breast cancer, CCL21-mediated recruitment of ILC3 to tumors stimulated the production of the CXCL13 by TME stromal cells, which in turn promoted ILC3-stromal interactions and production of the cancer cell motile factor RANKL. Depleting ILC3 or neutralizing CCL21, CXCL13, or RANKL was sufficient to decrease lymph node metastasis. Our findings establish a role for RORγt+ILC3 in promoting lymphatic metastasis by modulating the local chemokine milieu of cancer cells in the TME. Cancer Res; 77(5); 1083-96. ©2017 AACR.

PIM1 kinase regulates cell death, tumor growth and chemotherapy response in triple-negative breast cancer.

Triple-negative breast cancers (TNBCs) have poor prognosis and lack targeted therapies. Here we identified increased copy number and expression of the PIM1 proto-oncogene in genomic data sets of patients with TNBC. TNBC cells, but not nonmalignant mammary epithelial cells, were dependent on PIM1 for proliferation and protection from apoptosis. PIM1 knockdown reduced expression of the anti-apoptotic factor BCL2, and dynamic BH3 profiling of apoptotic priming revealed that PIM1 prevents mitochondrial-mediated apoptosis in TNBC cell lines. In TNBC tumors and their cellular models, PIM1 expression was associated with several transcriptional signatures involving the transcription factor MYC, and PIM1 depletion in TNBC cell lines decreased, in a MYC-dependent manner, cell population growth and expression of the MYC target gene MCL1. Treatment with the pan-PIM kinase inhibitor AZD1208 impaired the growth of both cell line and patient-derived xenografts and sensitized them to standard-of-care chemotherapy. This work identifies PIM1 as a malignant-cell-selective target in TNBC and the potential use of PIM1 inhibitors for sensitizing TNBC to chemotherapy-induced apoptotic cell death.