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Background: Heterozygous hotspot mutations in the RNA splicing factor SF3B1, occur in 3% of unselected breast cancers and are associated with oestrogen receptor (ER+) breast cancer (BC) where they are enriched in metastatic disease and are associated with a poor clinical outcome. SF3B1 mutations drive distinct signatures of alternative splicing through cryptic 3’ splice site selection leading to global transcriptomic and proteomic changes. The functional consequences of the mis-splicing events and resultant genetic vulnerabilities are poorly understood and precision medicine approaches that exploit these characteristics are not clinically available (Table 1). Methods: To understand the role of SF3B1 mutations in ER+ BC, we generated a series of SF3B1 mutant (SF3B1MUT) isogenic cell lines which were characterised using RNA-sequencing and high content mass-spectrometry proteomic profiling. SF3B1 interactome analysis was also performed using immunoprecipitation of SF3B1 followed by mass-spectrometry. The molecular consequences of aberrant splicing were investigated using a targeted screening approach of 280 genes predicted to be alternatively spliced in SF3B1MUT BC, while high-throughput drug screens were used to identify novel therapeutic options for patients with SF3B1MUT breast cancer using isogenic cells. Hits were validated in vitro and in vivo using cell line and patient derived xenografts. Results: Transcriptomic and proteomic profiling of SF3B1MUT cells identified global alternative 3’ splice site selection and subsequent proteomic changes induced by the mutations. Investigation of the SF3B1K700E interactome identified an enrichment of SF3B1K700E binding with ER, aberrant splicing of ER target genes, global rewiring of ER chromatin binding and resistance to endocrine therapy. Silencing of the aberrantly spliced candidate genes PPIH, TRIM37, HIGD1A, BRD9, and PHKG2 significantly enhanced the growth of the SF3B1 mutant cells, suggestive of a dose dependent tumour suppressive effect. Through synthetic-lethal drug screens we found that SF3B1MUT cells are selectively sensitive to PARP inhibitors. SF3B1MUT cells display a defective response to PARPi induced replication stress. Mechanistically, this occurs via defective ATR signalling in SF3B1MUT cells, which upon PARPi exposure leads to increased replication origin firing and loss of pChk1 (S317) induction. The resultant replication stress leads to failure to resolve DNA replication intermediates via the endonuclease MUS81 and cell cycle stalling at the G2/M checkpoint. These defects can be further targeted by ATM, CDK7 or FACT inhibition, when used in combination with PARPi treatment. This SF3B1MUT selective PARPi sensitivity is preserved across multiple cell lines and patient derived tumour models. In vivo, PARPi produce profound anti-tumour effects in multiple SF3B1MUT cancer models and eliminate distant metastases. Conclusions: Our integrative analysis reveals mechanistic insight into the role of SF3B1 mutations in endocrine therapy response in ER+ breast cancers, where altered SF3B1 induces ER-transcriptional re-programming. We further identified a robust synthetic-lethal relationship of mutant SF3B1 with PARP inhibition that is caused by a defective response to PARPi induced replication stress. Furthermore, we identified several potential selective combination strategies together with PARPi that are selective for SF3B1MUT cells. Together, these data provide the pre-clinical and mechanistic rationale for assessing already-approved PARPi in a biomarker-defined subset of advanced ER+ BC. Table 1. Identified potential therapies for SF3B1 mutant cancers from this study and the literature Citation Format: Phil Bland, Harry Saville, Abigail Read, Patty Wai, Gareth Muirhead, Lucinda Curnow, Jadwiga Nieminuszczy, Nivedita Ravindran, Marie John, Somaieh Hedayat, Holly Barker, James Wright, Lu Yu, Ioanna Mavrommati, Barrie Peck, Mark Allen, Patrycja Gazinska, Helen Pemberton, Aditi Gulati, Sarah Nash, Farzana Noor, Naomi Guppy, Ioannis Roxanis, Samantha Barlow, Helen Kalirai, Sarah Coupland, Ronan Broderick, Samar Alsafadi, Alexandre Houy, Marc-Henri Stern, Stephen Pettit, Jyoti Choudhary, Syed Haider, Wojciech Niedzwiedz, Christopher Lord, Rachael Natrajan. Mutations in the RNA Splicing Factor SF3B1 drive endocrine therapy resistance and confer a targetable replication stress response defect through PARP inhibition. [abstract]. In: Proceedings of the 2022 San Antonio Breast Cancer Symposium; 2022 Dec 6-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2023;83(5 Suppl):Abstract nr P6-10-05.

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.

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.

Enrichment analysis from TCGA RNA-seq and RPPA data comparing CREBBPaltered versus wild-type patients.

Supplementary Methods described

Time lapse microscopy experiment of sorted NKp46-ILC3 cells (CD3-, CD11c-, B220, NKp46-, CD127+, CD90.2+) co-cultured with MSC cells as described in Figure 2B. Low magnification (Ã-10) video shows the general clustering pattern of NKp46-ILC3 cells around the MSC cells over a duration of 10 hours.

Figure S1, Related to Figure 1 FACS and immunofluorescence validation of Lin-CD127+CD90.2+NKP46- gated ILC3 cells Figure S2, Related to Figure 2 ELISA quantification of CXCL13 and CCL21 chemokines levels in conditioned media (CM) obtained from the bone marrow derived MSC cell line (HS-5) and from the breast cancer cell line 4T1.2 cell line is shown. Figure S3, Related to Figure 2 Proliferation assay of ILC3 cells and ELISA quantification of CXCL13 and CCL21 from siRNA transfected MSC cells. Figure S4, Related to Figure 4 CXCR5 expression on MSC cells. Figure S5, Related to Figure 5 Identification of a RORγT+CD127+CD3- ILC3 cells within the tertiary lymphoid structures within breast cancers. Figure S6, Related to Figure 5 Expression of lymphoid chemokine and chemokine receptor genes in breast cancer datasets. Table S1, Related to Figure 5 Table S1: Clinico-pathological characteristics for the METABRIC sample.

Supplementary Figure legends

Supplementary Materials and Methods

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.

This article focuses on the application of wind speed data of 4 coastal areas of Baluchistan, that is, Gawadar, Jiwani, Ormara, and Pasni on 4-Component Rayleigh Mixture Model (4-CRMM) under Bayesian context. Type I right censoring scheme is used because it is popular in reliability theory and survival analysis. To accomplish the objective, the Bayes estimates (BEs) of the parameter of the mixture model along with their posterior risks (PRs) using informative prior (IP) and noninformative prior (NIP) are obtained. Hyperparameters are obtained by employing the prior predictive method. BEs are calculated under two distinct loss functions, squared error loss function (SELF) and modified squared error loss function (MSELF). The statistical properties and performance of the BEs under said loss functions are also evaluated by simulation study for different sample sizes.

Understanding of complex relationships among economic variables has much significance for investors, researchers and policy makers alike. This study is conducted to examine dynamic linkages among gold price, stock prices, exchange rate and interest rate nexus using monthly data of Pakistan economy ranging from 2001-1 to 2014–12. Search of the best model motivates the use of Bayesian inference. Hence, the study is also used to compare performance of classical VAR model and Bayesian VAR model under four types of priors. It may be considered another significant contribution in terms of methodological framework. All the four variables are nonstationary at level but stationary at first difference. However, no long-run relationship among the variables is found by employing three cointegration tests, i.e. JJ test without considering structural break, GH test considering one unknown structural break and HJ test allowing two unknown structural breaks. Hence short-run relationship is analyzed in the study. Bayesian VAR model under independent normal inverse Wishart priors is selected as the best model which is then used to conduct impulse response analysis. Inverse bilateral relationships between stock prices and gold price as well as between rupee value and gold price are determined where as positive bilateral relationship between stock prices and rupee value is explored. It implies that stock prices and rupee value move downward during recessionary periods but gold becomes more pretty and vice versa also hold. Hence, gold is not only considered as safe haven but it is also considered as an alternative investment during adverse fluctuations in stock and foreign exchange markets of Pakistan. Changes in stock prices and rupee value are negatively responded by monetary policy makers in Pakistan but changes in gold prices are not considered by monetary authorities. Results also reveal that monetary policy actions significantly and adversely affect the three markets under consideration. Direct relationship between nominal interest rate and exchange rate in Pakistan conform to the International fisher effect theory.

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.

Burning velocity of different chemicals is estimated using a model from mixed population considering inverted Kumaraswamy (IKum) distribution for component parts. Two estimation techniques maximum likelihood estimation (MLE) and Bayesian analysis are applied for estimation purposes. BEs of a mixture model are obtained using gamma, inverse beta prior, and uniform prior distribution with two loss functions. Hyperparameters are determined through the empirical Bayesian method. An extensive simulation study is also a part of the study which is used to foresee the characteristics of the presented model. Application of the IKum mixture model is presented through a real dataset. We observed from the results that Linex loss performed better than squared error loss as it resulted in lower risks. And similarly gamma prior is preferred over other priors.

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.

In this article, Maximum likelihood estimation (MLE) and Bayesian estimation for Rayleigh distribution using progressive type-II censoring in the presence of outliers is considered. Inverse Gamma prior and Jeffreys prior are used for Bayesian estimation. Squared error loss function (SELF), precautionary loss function (PLF) and K-loss function (KLF) are used for obtaining the expressions of Bayes estimators and posterior risks. Credible intervals are also derived. A simulation study is presented to discuss the behavior of Bayes estimators. Applicability of the undertaken study is highlighted using three real data sets.

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.

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.

A large number of models have been derived from the two-parameter Weibull distribution including the inverse Weibull (IW) model which is found suitable for modeling the complex failure data set. In this paper, we present the Bayesian inference for the mixture of two IW models. For this purpose, the Bayes estimates of the parameters of the mixture model along with their posterior risks using informative as well as the non-informative prior are obtained. These estimates have been attained considering two cases: (a) when the shape parameter is known and (b) when all parameters are unknown. For the former case, Bayes estimates are obtained under three loss functions while for the latter case only the squared error loss function is used. Simulation study is carried out in order to explore numerical aspects of the proposed Bayes estimators. A real-life data set is also presented for both cases, and parameters obtained under case when shape parameter is known are tested through testing of hypothesis procedure.

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

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.

In this article, we present Bayesian estimation of a shifted exponential distribution assuming progressive type-II censoring with random removals. Bayes estimators and their respective posterior risks are derived under the squared error loss function and the precautionary loss function. Moreover, the credible intervals and expected experiment time along with the Bayesian predictive intervals for one- and two-sample cases are also discussed. A comparison of the expected experiment time under complete and type-II progressive censoring is also a part of this study. Finally, a real-life example is provided to illustrate the proposed methodology.

In order to identify novel tumor drivers and gene addictions in breast cancer we have recently completed an integrated in silico/in vitro analysis of gene copy-number alterations and gene-expression profiles in a Triple Negative Breast Cancer-enriched cohort. An amplified and overexpressed gene that appeared to be a driver required for breast cancer cell proliferation is GPHR/GPR89. Several lines of evidence have recently suggested GPHR to be an anion channel, resident in the Golgi, where it controls intraluminal pH. Perturbation of GPHR function leads to altered secretory protein modification and impairment of intracellular transport. Additional data obtained in non-mammalian systems suggest that the localization of GPHR is wider and includes the endoplasmic reticulum (ER). Here, we show that GPHR is amplified and highly expressed across the breast cancer subtypes in our cohort, which we validate in the publicly available TCGA and METABRIC datasets. Using orthogonal characterization by both siRNA-shRNA and CRISPR/Cas9 gene editing, we demonstrate that GPHR down regulation impairs breast cancer cell proliferation and clonogenic ability. To further exclude the possibility that the observed phenotype was due to an “off target” effect, we also performed a rescue of function experiment overexpressing a GPHR protein resistant to GPHR shRNA that confirmed specificity. Importantly, breast cancer spheroids inducibly overexpressing GPHR are shown to have an increased area compared to control spheroids, demonstrating an important role of GPHR in breast cancer cell proliferation. Furthermore, by gradient sucrose subcellular fractionations and immunofluorescence analysis, we show that GPHR is localized in the ER of breast cancer cells. Unfolded protein response (UPR) signatures based on first-degree protein-protein interactions indicate that GPHR is positively correlated with IRE1α and negatively correlated with ATF4/CHOP networks. GPHR is also positively correlated with the XBP1 gene signature. We then further demonstrate that over expression or down regulation of GPHR are able to modulate the IRE1α/XBP1 network of proteins. In summary, in order to sustain uncontrolled growth, breast cancer cells undergo significant stress due to accelerated metabolism, deficient nutrient provision and oxidative stress. UPR signaling and GPHR expression are then essential to protect cells and to allow tumor growth by reducing protein synthesis and favoring chaperonine functions. Here we demonstrate that GPHR is over expressed across the breast cancer subtypes where it controls IRE1α/XBP1 network, and, therefore, can be a novel target for breast cancer therapy as malignant breast cells overexpressing GPHR are selectively dependent on GPHR expression. Citation Format: Riccardo Ferro, Pierfrancesco Marra, Ana Mendes Pereira, Virinder Reen, Cynthia Prince, Sumi Mathew, Alessandra Facchetti, Priyanka Ghongane-Salpe, Sedigeh Kareemaghay, Patrycja Gazinska, David Robertson, Farzana Noor, Fara Braso' Maristany, Daniel Weekes, Dragomir Krastev, Tencho Tenev, Hasan Mirza, Nirmesh Patel, Anita Grigoriadis, Andrew Tutt. The anion channel GPHR/GPR89 regulates protein-folding homeostasis by regulating the IRE1α pathway in breast cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr 443.

Triple-negative breast cancers (TNBCs) have poor prognosis and lack targeted therapies. Interrogation of genomic datasets identified increased PIM1 copy number-driven expression in TNBC. RNA interference in breast cancer and non-malignant mammary epithelial cell models revealed a PIM1 dependency in TNBC cells for proliferation and apoptotic protection, absent in non-malignant cells. PIM1 knockdown reduced BCL2 expression, and dynamic BH3 profiling analysis revealed that PIM1 prevents mitochondrial-mediated apoptosis in TNBC cell lines. PIM1 expression associates with several MYC-transcriptional signatures and promotes cell population growth through regulation of c-MYC and transcription of MYC-targets, including MCL1. The pan-PIM kinase inhibitor AZD1208 inhibited growth and sensitized TNBC cell lines, xenografts and patient-derived xenografts to standard of care chemotherapy. We identify PIM1 as a malignant cell-selective target in TNBC, illustrating relationships with MYC activation, regulation of anti-apoptotic BCL2 and MCL1, established TNBC oncogenic proteins SHP2 and EPHA2 and cell cycle inhibitor p27. Finally we identify a potential use of PIM1 inhibitors to abrogate TNBC's high threshold to TNBC standard of care chemotherapy induced apoptotic cell death.

The importance of wireless communications in today's telecommunications industry is indubitable. Wireless technologies are used in almost every aspect of our everyday life. Universal Mobile Telecommunications System (UMTS) technology has already implemented 3G communication standard for mobile communications. Power amplifiers are the most power consuming unit in wireless communication systems. The power amplifiers used in UMTS devices need to be highly efficient. Improved efficiency not only extends the battery life but also reduces the DC power consumption, transmitter size and weight. Although the power amplifiers used in existing second generation GSM (Global System for Mobile Communications) transmitters are highly efficient, they cannot be applied to UMTS/WCDMA since GSM uses the constant envelope feature of GMSK (Gaussian Minimum Shift Keying) modulation which introduces phase variations only. In UMTS, a WCDMA system with QPSK modulation is used where both phase and amplitude variations are introduced by the modulation. The power amplifiers designed for WCDMA need to satisfy the contradicting operation requirement between linearity and efficiency. In this thesis, a highly efficient class F power amplifier has been designed for WCDMA band with a center frequency of 2.14 GHz and bandwidth of 5 MHz using GaN transistor. The amplifier has been simulated using a high frequency circuit simulator namely, the Agilent Advanced Design System (ADS). The simulated results have shown a Power Added Efficiency (PAE) of 76.8% for an optimum input power of 30 dBm. The amplifier was then fabricated and measured. Measurement has shown a PAE of 75.9% for an optimum input power of 29.6 dBm which is in good accordance with the simulated results. Based on a literature review, and to the best of our knowledge, our circuit exhibited one of the highest measured PAE for a GaN class-F amplifier working at 2.14 GHz. The value of third and fifth order IM products of the designed class F PA is -13 dBc and -21 dBc respectively at peak power and -28.5 dBc and -43 dBc respectively at 6 dB back-off from peak power.

Triple negative breast cancers (TNBCs) lack oestrogen (ER), progesterone (PR) and human epidermal growth factor 2 (HER2) receptors, and have limited targeted treatment options. Large scale genomic and transcriptomic studies have advanced our understanding of the changes which occur in TNBCs. However, the substantial number of copy number and gene expression alterations present in TNBCs makes it difficult to identify putative drivers, biomarkers and/or therapeutic targets of the disease. To overcome this problem, we have carried out an integrative computational and RNAi based approach to identify genes required for proliferation of TNBC. Copy number and gene expression alterations were analysed using Affymetrix Human Exon HTS1.0 and SNP6.0 data of 152 primary breast tumours enriched for a TNBC phenotype and 9 normal breast epithelium. These analyses revealed 141 candidate genes whose upregulated gene expression is copy number driven in TNBC. The functional dependence on each of these genes was subsequently examined using RNAi in an array of 17 breast cancer and non-malignant cell lines using 6-8 cell lines per gene covering the widest possible range of expression levels for that gene. We validated a malignant cell specific functional dependence on 37 of the 141 genes using this method. STRING analysis of validated hits reveals a subset of genes involved in the process of cell division and mitosis including the previously characterised mitotic kinase TTK. Of these, we further validated KIFC1 (HSET) which is known to play a role in clustering supernumerary centrosomes, a common occurrence in breast cancer. We show that siRNA and shRNA mediated depletion of KIFC1 decreases cell viability and clonogenic ability specifically in centrosome amplified cell lines, which can be rescued upon introduction of an si/shRNA resistant KIFC1. KIFC1 depletion also produces a high level of catastrophic multipolar mitoses in centrosome amplified but not in non-amplified cell lines. Furthermore, in-vivo studies show that inducible depletion of KIFC1 suppresses tumour growth of centrosome amplified cell line xenografts. Our work has identified and functionally validated novel drivers, and potential therapeutic targets in TNBC. The data presented here shows KIFC1, a druggable kinesin motor protein is a promising target for therapeutic intervention being expressed through gene copy gain in a significant proportion of TNBCs. We validate its role in cancer-specific amplified centrosome clustering showing KIFC1 plays an essential role in aiding the survival of breast cancer cells that have supernumerary centrosomes in both in-vitro and in-vivo contexts. Citation Format: Nirmesh S. Patel, Konstantinos Drosopoulos, Daniel Weekes, Elodie Noel, Hasan Mirza, Mamunur Rashid, Emanuele de Rinaldis, Fara Brasó Maristany, Sumi Mathew, Erika Francesch Domenech, Patrycja Gazinska, Farzana Noor, Jelmar Quist, Rebecca Marlow, Anita Grigoriadis, Spiros Linardopoulos, Andrew N. Tutt. An integrated copy number and gene expression genomics analysis and RNAi approach identifies and validates the KIFC1 kinesin as a malignant cell selective target in triple negative breast cancer. [abstract]. In: Proceedings of the 107th Annual Meeting of the American Association for Cancer Research; 2016 Apr 16-20; New Orleans, LA. Philadelphia (PA): AACR; Cancer Res 2016;76(14 Suppl):Abstract nr 67.

The success of medication treatment is dependent on a patient’s adherence to the medication regimen and non-adherence amongst psychiatric patients is associated with poor clinical outcomes and high resource utilization. The aim of this study was to assess the levels of medication adherence in psychiatric outpatients and explore factors that influence adherence. Adult, psychiatric outpatients were assessed to (1) determine medication adherence and (2) identify factors that might impact on adherence, using the Morisky Medication Adherence Questionnaire. The impact of socio- demographic factors as well as treatment related factors were considered. 95 outpatients participated in the study. The eight item Morisky medication adherence scale indicated high adherence levels amongst 12.6%, moderate adherence levels amongst 50.8%, and low adherence levels amongst 37% of participants. Significant predictors of adherence to psychiatric treatment were age (p=0.045) and race (p=0.055). The impact of socio-demographic variables on adherence, such as the type of condition, employment status and educational level, were insignificant. Adherence levels amongst psychiatric outpatients were found to be acceptable, with race and age predictors of adherence levels in this study population. Key words: Adherence, psychiatry, morisky scale, outpatients, race, age.

The method of paired comparisons may be regarded as a special rank order technique. It is a method long used in psychological experimentation and is well adapted to sensory difference testing. This study deals with estimation and testing of the parameters of the Rao-Kupper (1967) model for paired comparisons which allows for tied observations in paired comparison experiments using informative prior. An elicitation of the hyper parameters is carried out. Predictive probabilities that one treatment would be preferred to other treatment in a future single comparison are determined. Graphs for the marginal posterior densities are presented. All calculations are based on numerical integration technique and Gibbs sampling procedure. Appropriateness of the model is checked which declares it a good fit.