Search

Supplementary Table 2 from NFBD1/MDC1 Regulates Cav1 and Cav2 Independently of DNA Damage and p53

Supplementary Legends for Figure 1 and Tables 1-2 from NFBD1/MDC1 Regulates Cav1 and Cav2 Independently of DNA Damage and p53

Supplementary Table 1 from NFBD1/MDC1 Regulates Cav1 and Cav2 Independently of DNA Damage and p53

Supplementary Figure 1 from NFBD1/MDC1 Regulates Cav1 and Cav2 Independently of DNA Damage and p53

Supplemental Figure 1. Consort Diagram 03-311. Supplemental Figure 2. Consort Diagram 211B. Supplemental Figure 3. Subtype-specific changes in Immune Index upon brief-exposure to nab-paclitaxel in the 211B trial. Supplemental Figure 4. Evaluation of the Immune Index upon brief-exposure to trastuzumab in the 03-311 and 211B trials according to ER/PR status. Supplemental Figure 5. Evaluation of the Immune Index upon brief-exposure to nab-paclitaxel in the 211B trial according to ER/PR status. Supplemental Figure 6. Correlation between Immune Index and tumor content. Supplemental Figure 7. Association of CD4+ Th1 and Treg signatures with response. Supplemental Table 1. Immune Index genes discriminative of response at the post-exposure timepoint in the discovery (03-311) and validation (211B) datasets. Supplemental Table 2. Immune cell subset signatures discriminative of response at baseline and post-exposure timepoints in the discovery (03-311) and validation (211B) datasets. Supplemental Table 3. CD8+ T-cell cytolytic activity genes discriminative of response at the post-exposure timepoint in the discovery (03-311) and validation (211B) datasets.

Purpose: Recent data suggest that intrinsic subtype and immune cell infiltration may predict response to trastuzumab-based therapy. We studied the interaction between these factors, changes in immune signatures following brief exposure to trastuzumab, and achievement of pathologic complete response (pCR) to subsequent preoperative trastuzumab and chemotherapy in HER2-positive breast cancer.Experimental Design: In patients enrolled on two multicenter trials (03-311 and 211B), tumor core biopsies were obtained at baseline and after brief exposure to single-agent trastuzumab or nab-paclitaxel. Gene expression profiles were assessed to assign PAM50 subtypes, measure immune cell activation, and were correlated with response.Results: The pCR rate was significantly higher in HER2-enriched tumors in the Discovery, 03-311 (36%, P = 0.043) dataset, as compared with other subtypes, which validated in 211B (50%, P = 0.048). Significant increases in a signature of immune cell admixture (Immune Index) were observed only following brief exposure to trastuzumab in HER2-enriched tumors (Discovery/03-311, P = 0.05; Validation/211B, P = 0.02). Increased Immune Index was predictive of response after brief exposure (03-311, P = 0.03; 211B, P = 0.04), but not at baseline, in addition to increased expression of a CD4+ follicular helper T-cell signature (03-311, P = 0.05; 211B, P = 0.04). Brief exposure to trastuzumab significantly increased gene expression of the T-cell marker PD-1 in HER2-enriched tumors (Discovery/03-311, P = 0.045) and PD-1 positivity by IHC (Validation/211B, P = 0.035).Conclusions: Correlations between pCR rates, increases in Immune Index and markers of T-cell activity following brief exposure to trastuzumab in HER2-enriched tumors provide novel insights into the interaction between tumor biology, antitumor immunity, and response to treatment, and suggest potential clinically useful biomarkers in HER2+ breast cancers. Clin Cancer Res; 22(13); 3249–59. ©2016 AACR.

Objectives A novel graph data model of non-small cell lung cancer clinical and genomic data has been constructed with two aims: (1) provide a suitable model for facilitating graph analytics within the Neo4j framework or through tools which can interact through existing Neo4j APIs; and (2) provide a base model extensible to other cancer types and additional datasets such as those derived from electronic health records and other real world sources. Data description Clinical and genomic data integrated with a novel property graph database schema from publicly available datasets and analyses based on The Cancer Genome Atlas lung cancer datasets augmented by with subgraphs patient-patient social network from similarity and correlation as well as individual based biological networks.

PURPOSE Increasingly broad patient groups are being treated with immune checkpoint inhibitors (ICIs) in clinical practice, but few studies have assessed their usage and outcomes in large, comprehensive real-world cohorts. We identified patients who received ICIs in the Veterans Affairs (VA) health care system and described patient characteristics and survival outcomes across multiple indications. METHODS We conducted a retrospective analysis using electronic health record data from VA facilities nationwide. Overall survival (OS) from time of ICI initiation for key indications was estimated by Kaplan-Meier. We also stratified OS by frailty status, as defined by a surrogate index developed in VA data. For select indications, we further compared outcomes to historic and concurrent control patients treated with standard-of-care regimens at the VA. RESULTS We identified 11,888 patients who were treated with ICIs and determined the cancer type and indication for which they were treated. The cohort is enriched for patient groups that are under-represented in pivotal clinical trials (PCTs), including older, non-White, and/or higher disease burdened patients. Generally, OS observed in the VA cohort is lower than that reported in PCTs. After stratifying VA patients by frailty status, OS among nonfrail patients is more similar to OS reported in PCTs for some indications. Compared with internal VA control cohorts, patients treated with ICIs generally exhibited longer OS for all indications considered. CONCLUSION This study describes ICI outcomes across multiple tumor types in a real-world population at the VA. For most indications, real-world survival outcomes are observed to be lower than those reported in PCTs, but patients receiving ICIs still achieve longer survival relative to patients receiving standard of care.

Background Emerging data suggest variability in susceptibility and outcome to coronavirus disease 2019 (COVID-19) infection. Identifying risk factors associated with infection and outcomes in cancer patients is necessary to develop healthcare recommendations. Methods We analyzed electronic health records of the US Veterans Affairs Healthcare System and assessed the prevalence of COVID-19 infection in cancer patients. We evaluated the proportion of cancer patients tested for COVID-19 who were positive, as well as outcome attributable to COVID-19, and stratified by clinical characteristics including demographics, comorbidities, cancer treatment, and cancer type. All statistical tests are 2-sided. Results Of 22 914 cancer patients tested for COVID-19, 1794 (7.8%) were positive. The prevalence of COVID-19 was similar across age. Higher prevalence was observed in African American (15.0%) compared with White (5.5%; P < .001) and in patients with hematologic malignancy compared with those with solid tumors (10.9% vs 7.8%; P < .001). Conversely, prevalence was lower in current smokers and patients who recently received cancer therapy ( Conclusion Preexistence of cancer affects both susceptibility to COVID-19 infection and eventual outcome. The overall COVID-19–attributable mortality in cancer patients is affected by age, comorbidity, and specific cancer types; however, race or recent treatment including immunotherapy do not impact outcome.

BackgroundEmerging data suggest variability in susceptibility and outcome to Covid-19 infection. Identifying the risk-factors associated with infection and outcomes in cancer patients is necessary to develop healthcare recommendations.MethodsWe analyzed electronic health records of the US National Veterans Administration healthcare system and assessed the prevalence of Covid-19 infection in cancer patients. We evaluated the proportion of cancer patients tested for Covid-19 and their confirmed positivity, with clinical characteristics, and outcome, and stratified by demographics, comorbidities, cancer treatment and cancer type.ResultsOf 22914 cancer patients tested for Covid-19, 1794 (7.8%) were positive. The prevalence of Covid-19 was similar across all ages. Higher prevalence was observed in African-American (AA) (15%) compared to white (5.5%; PConclusionPre-existence of cancer affects both susceptibility to Covid-19 infection and eventual outcome. The overall Covid-19 attributable mortality in cancer patients is affected by age, co-morbidity and specific cancer types, however, race or recent treatment including immunotherapy does not impact outcome.FundingsVA Office of Research and Development and National Institutes of Health.

Importance Patients with cancer are at increased risk for severe COVID-19, but it is unknown whether SARS-CoV-2 vaccination is effective for them. Objective To determine the association between SARS-CoV-2 vaccination and SARS-CoV-2 infections among a population of Veterans Affairs (VA) patients with cancer. Design, Setting, and Participants Retrospective, multicenter, nationwide cohort study of SARS-CoV-2 vaccination and infection among patients in the VA health care system from December 15, 2020, to May 4, 2021. All adults with solid tumors or hematologic cancer who received systemic cancer-directed therapy from August 15, 2010, to May 4, 2021, and were alive and without a documented SARS-CoV-2 positive result as of December 15, 2020, were eligible for inclusion. Each day between December 15, 2020, and May 4, 2021, newly vaccinated patients were matched 1:1 with unvaccinated or not yet vaccinated controls based on age, race and ethnicity, VA facility, rurality of home address, cancer type, and treatment type/timing. Exposures Receipt of a SARS-CoV-2 vaccine. Main Outcomes and Measures The primary outcome was documented SARS-CoV-2 infection. A proxy for vaccine effectiveness was defined as 1 minus the risk ratio of SARS-CoV-2 infection for vaccinated individuals compared with unvaccinated controls. Results A total of 184 485 patients met eligibility criteria, and 113 796 were vaccinated. Of these, 29 152 vaccinated patients (median [IQR] age, 74.1 [70.2-79.3] years; 95% were men; 71% were non-Hispanic White individuals) were matched 1:1 to unvaccinated or not yet vaccinated controls. As of a median 47 days of follow-up, 436 SARS-CoV-2 infections were detected in the matched cohort (161 infections in vaccinated patients vs 275 in unvaccinated patients). There were 17 COVID-19-related deaths in the vaccinated group vs 27 COVID-19-related deaths in the unvaccinated group. Overall vaccine effectiveness in the matched cohort was 58% (95% CI, 39% to 72%) starting 14 days after the second dose. Patients who received chemotherapy within 3 months prior to the first vaccination dose were estimated to have a vaccine effectiveness of 57% (95% CI, -23% to 90%) starting 14 days after the second dose vs 76% (95% CI, 50% to 91%) for those receiving endocrine therapy and 85% (95% CI, 29% to 100%) for those who had not received systemic therapy for at least 6 months prior. Conclusions and Relevance In this cohort study, COVID-19 vaccination was associated with lower SARS-CoV-2 infection rates in patients with cancer. Some immunosuppressed subgroups may remain at early risk for COVID-19 despite vaccination, and consideration should be given to additional risk reduction strategies, such as serologic testing for vaccine response and a third vaccine dose to optimize outcomes.

Introduction: Nuclear protein in testis midline carcinoma (NMC) is a rare and extremely aggressive carcinoma (median survival < 7 months) with no effective treatment options. CUDC-907 is a novel small molecule inhibitor of histone deacetylase (HDAC) and phosphoinositide 3-kinase (PI3K) enzymes currently being investigated in multiple tumor types, including NMC. Case Report: A 61-year old female NMC patient enrolled on study CUDC-907-102 (NCT02307240) after rapidly progressing through two prior treatments. The patient’s assessable sites of disease consisted of right pleural effusion, right hilar soft tissue, and segment IV liver. Treatment was well tolerated with toxicities primarily consisting of manageable diarrhea and thrombocytopenia. The patient remains on active treatment after more than 32 months of stable disease. Discussion: Dysregulation of MYC in NMC is believed to play a central role in pathogenesis. CUDC-907 has demonstrated potent suppression of MYC expression and anti-tumor activity in preclinical NMC models, providing a mechanistic rationale for the prolonged disease stabilization observed here. The treatment of additional NMC patients with CUDC-907 is needed to further evaluate this promising report. Conclusion: This case demonstrates a rare success in the treatment of a devastating disease using only a novel small molecule, warranting further investigation of CUDC-907 in NMC.

Introduction Coronavirus disease 2019 (COVID-19), caused by the SARS-CoV-2 virus, is particularly serious in patients with multiple myeloma (MM), with estimated mortality of over 30% in several studies. In the general population, SARS-CoV-2 vaccination has been demonstrated to be an effective approach to preventing infection. However, patients with MM were not included in vaccination trials. Recent studies suggest that patients with compromised immune systems exhibit reduced antibody response to SARS-CoV-2 vaccination, and MM patients are often immunocompromised both due to MM itself and due to MM treatment. Thus, the objective of this retrospective cohort study in the national Veterans Affairs (VA) healthcare system was to evaluate the real-world effectiveness of SARS-CoV-2 vaccination to prevent COVID-19 infection in MM patients during the 140-day period following initial vaccine availability. Methods This is a multicenter study of SARS-CoV-2 infection among vaccinated and unvaccinated patients at VA hospitals nationwide during the period from 12/15/2020 to 5/4/2021. We identified a cohort of MM patients who were alive and without prior SARS-CoV-2 infection on their date of vaccination or inclusion as a control. For added comparison with a less immunocompromised population, we also identified a cohort of cancer survivors, defined as patients with any solid or hematologic malignancy who had been treated with systemic cancer-directed therapy subsequent to 8/15/2010, but had not been treated with such therapy in the 6 months prior to vaccination or inclusion as a control, and were alive and without prior SARS-CoV-2 infection on that date. Vaccinated patients were exactly matched 1:1 to unvaccinated controls on race, VA facility, rurality of home address, cancer type, and treatment timing and modality with minimum distance matching on age. The primary exposure was receipt of a SARS-CoV-2 vaccine. The primary outcome was laboratory-confirmed SARS-CoV-2 infection. Vaccination effectiveness was defined as 1 minus the risk ratio of SARS-CoV-2 infection for vaccinated individuals compared to unvaccinated controls. Results 6,891 MM patients met eligibility criteria and 4,367 were vaccinated during the study period. Of those, 1,606 vaccinated MM patients were matched 1:1 to 1,606 unvaccinated or not yet vaccinated controls. In addition, for comparison, 2,476 vaccinated cancer survivors were matched 1:1 to 2,476 unvaccinated or not yet vaccinated controls. Median follow-up was 44 days among MM patients and 46 days among cancer survivors. Vaccine effectiveness in the matched cohort of MM patients was 22.2% (95% CI, -133 to 82.7%) starting 14 days after the second dose. In contrast, effectiveness was 82.3% (95% CI 16.4 to 100%) starting 14 days after the second dose in the matched cohort of cancer survivors. Among vaccinated MM patients in the matched cohort, 14 (8.7 per 1000 patients) were infected with SARS-CoV-2 subsequent to vaccination. Among vaccinated cancer survivors in the matched cohort, 10 (4.0 per 1000 patients) were infected subsequent to vaccination. Conclusion Vaccination is an effective strategy for preventing SARS-CoV-2. However, effectiveness may be reduced in patients with MM, likely due to a co-existing immunosuppression both due to the disease process as well as associated therapy. Future studies are needed to evaluate the relationship between MM disease states, types of therapy used and treatment timing that may impact vaccine effectiveness, and to also determine if MM patients would benefit from post-vaccination serologies or a booster vaccination. Disclosures Branch-Elliman: Gilead Pharmaceuticals: Research Funding. Brophy: Novartis: Research Funding. Munshi: Pfizer: Consultancy; Legend: Consultancy; Novartis: Consultancy; Adaptive Biotechnology: Consultancy; Karyopharm: Consultancy; Celgene: Consultancy; Oncopep: Consultancy, Current equity holder in publicly-traded company, Other: scientific founder, Patents & Royalties; Abbvie: Consultancy; Takeda: Consultancy; Amgen: Consultancy; Janssen: Consultancy; Bristol-Myers Squibb: Consultancy.

Background: Data is lacking about SARS-CoV-2 vaccination effectiveness in patients with cancer, particularly those on systemic therapy. This retrospective cohort study in the US national Veterans Affairs (VA) healthcare system reports the effectiveness of SARS-CoV-2 vaccination in cancer patients on and off active therapy during the first 140 days following administration. Methods: This is a multicenter study of SARS-CoV-2 infection among vaccinated and unvaccinated Veterans vaccinated during the period from 12/15/2020 to 5/4/2021. Veterans with solid or hematologic malignancy who received systemic cancer-directed therapy at the VA at least one time between 8/15/2010 to 5/4/2021 were included. Vaccinated patients were exactly matched 1:1 to an unvaccinated control on race, VA facility, rurality of home address, cancer type, and treatment timing and modality with minimum distance matching on age. The primary exposure was receipt of a SARS-CoV-2 vaccine. The primary outcome was laboratory-confirmed SARS-CoV-2 infection. Vaccination effectiveness was defined as 1 minus the risk ratio of SARS-CoV-2 infection for vaccinated individuals compared to unvaccinated controls. Results: 184,485 patients met eligibility criteria and 113,796 were vaccinated during the study period. Of these, 29,152 vaccinated patients were matched 1:1 to 29,152 unvaccinated or not yet vaccinated controls. As of a median 47 days of follow-up, overall vaccine effectiveness in the matched cohort was 58% (95% CI, 39 to 72%) starting 14 days after the second dose. Patients on chemotherapy within three months prior to first vaccination dose exhibited a 14-day post-second dose effectiveness of 57% (95% CI -23 to 90%), versus 76% (95% CI 50 to 91%) for those on endocrine therapy and 85% (95% CI 29 to 100%) for those off systemic therapy for at least six months prior. Conclusions: Vaccination is an effective strategy for preventing COVID-19 in cancer patients. However, effectiveness may be reduced in patients actively receiving immunosuppressive systemic therapy. Future study is needed to determine if these patients would benefit from post-vaccination serologies and/or a booster vaccination following completion of therapy. Legal entity responsible for the study: Nathanael Fillmore. Funding: Has not received any funding. Disclosure: W. Branch-Elliman: Financial Interests, Institutional, Funding: Gilead. G. Parmigiani: Financial Interests, Personal, Leadership Role: Phaeno Biotechnology. M. Brophy: Financial Interests, Personal, Research Grant: Novartis. N. Munshi: Financial Interests, Personal, Advisory Role: Celgene;Financial Interests, Personal, Advisory Role: Janssen;Financial Interests, Personal, Advisory Role: AbbVie;Financial Interests, Personal, Advisory Role: Takeda;Financial Interests, Personal, Member of the Board of Directors: OncoPep. All other authors have declared no conflicts of interest.

Background: There is wide interest in developing prognostic models in non–small-cell lung cancer (NSCLC) due to the heterogeneity of the disease. Models developed at other healthcare institutions may not be directly applicable for patients treated at the Department of Veterans Affairs (VA). External validation of a candidate prognostic model among VA patients would be crucial before it can be implemented to aid clinical decision-making. Methods: A prognostic model for mortality developed in the Military Health System (MHS) was applied to data from the VA Precision Oncology Data Repository (VA-PODR), which is available to researchers inside and outside the VA at the Veterans Precision Oncology Data Commons (VPODC). Measures of discrimination and calibration were calculated for the MHS model. The MHS model was also refitted in VA-PODR data using the same risk factors to compare the effect of specific factors and predictive performance when the model is developed using VA data. Results: Time-dependent AUC of the MHS prognostic model was 0.788, 0.806, 0.780, and 0.779 for predicting survival at 1, 2, 3, and 5 years following diagnosis, respectively. Significant discrepancies were found between predicted and observed rates of survival, particularly for later years. When the model is refit in VA-PODR data, it achieved cross-validated AUCs of 0.739, 0.773, 0.769, and 0.807 at the same time points, and discrepancies between predicted and observed survival were reduced. Conclusions: Validation of the MHS prognostic model in VA-PODR demonstrates that its discrimination remains strong when applied to VA patients. Nevertheless, further calibration to VA data may be needed to improve its risk estimation performance. This study highlights the utility of VA-PODR and the VPODC as a national resource for developing analytic tools that are well adapted to the Veteran population.

The Department of Veterans Affairs (VA) has a strong track record providing high-quality, evidence-based care to cancer patients. In order to accelerate discoveries that will further improve care for Veterans with cancer, the VA has partnered with the Center for Translational Data Science at the University of Chicago and the Open Commons Consortium to establish a data sharing platform, the Veterans Precision Oncology Data Commons (VPODC). The VPODC makes clinical, genomic, and imaging data from the VA available to the research community at large. In this paper, we detail our motivation for data sharing, describe the VPODC, and outline our collaboration model. By transforming VA data into a national resource for research in precision oncology, the VPODC seeks to foster innovation through collaboration and resource sharing that will ultimately lead to improved care for Veterans with cancer.

Upregulation of MYC is a common driver event in human cancers, and some tumors depend on MYC to maintain transcriptional programs that promote cell growth and proliferation. Preclinical studies have suggested that individually targeting upstream regulators of MYC, such as histone deacetylases (HDAC) and phosphoinositide 3-kinases (PI3K), can reduce MYC protein levels and suppress the growth of MYC-driven cancers. Synergy between HDAC and PI3K inhibition in inducing cancer cell death has also been reported, but the involvement of MYC regulation is unclear. In this study, we demonstrated that HDAC and PI3K inhibition synergistically downregulates MYC protein levels and induces apoptosis in “double-hit” (DH) diffuse large B-cell lymphoma (DLBCL) cells. Furthermore, CUDC-907, a small-molecule dual-acting inhibitor of both class I and II HDACs and class I PI3Ks, effectively suppresses the growth and survival of MYC-altered or MYC-dependent cancer cells, such as DH DLBCL and BRD–NUT fusion-positive NUT midline carcinoma (NMC) cells, and MYC protein downregulation is an early event induced by CUDC-907 treatment. Consistently, the antitumor activity of CUDC-907 against multiple MYC-driven cancer types was also demonstrated in animal models, including DLBCL and NMC xenograft models, Myc transgenic tumor syngeneic models, and MYC-amplified solid tumor patient-derived xenograft (PDX) models. Our findings suggest that dual function HDAC and PI3K inhibitor CUDC-907 is an effective agent targeting MYC and thus may be developed as potential therapy for MYC-dependent cancers. Mol Cancer Ther; 16(2); 285–99. ©2016 AACR.

Purpose: Recent data suggest that intrinsic subtype and immune cell infiltration may predict response to trastuzumab-based therapy. We studied the interaction between these factors, changes in immune signatures following brief exposure to trastuzumab, and achievement of pathologic complete response (pCR) to subsequent preoperative trastuzumab and chemotherapy in HER2-positive breast cancer. Experimental Design: In patients enrolled on two multicenter trials (03-311 and 211B), tumor core biopsies were obtained at baseline and after brief exposure to single-agent trastuzumab or nab-paclitaxel. Gene expression profiles were assessed to assign PAM50 subtypes, measure immune cell activation, and were correlated with response. Results: The pCR rate was significantly higher in HER2-enriched tumors in the Discovery, 03-311 (36%, P = 0.043) dataset, as compared with other subtypes, which validated in 211B (50%, P = 0.048). Significant increases in a signature of immune cell admixture (Immune Index) were observed only following brief exposure to trastuzumab in HER2-enriched tumors (Discovery/03-311, P = 0.05; Validation/211B, P = 0.02). Increased Immune Index was predictive of response after brief exposure (03-311, P = 0.03; 211B, P = 0.04), but not at baseline, in addition to increased expression of a CD4+ follicular helper T-cell signature (03-311, P = 0.05; 211B, P = 0.04). Brief exposure to trastuzumab significantly increased gene expression of the T-cell marker PD-1 in HER2-enriched tumors (Discovery/03-311, P = 0.045) and PD-1 positivity by IHC (Validation/211B, P = 0.035). Conclusions: Correlations between pCR rates, increases in Immune Index and markers of T-cell activity following brief exposure to trastuzumab in HER2-enriched tumors provide novel insights into the interaction between tumor biology, antitumor immunity, and response to treatment, and suggest potential clinically useful biomarkers in HER2+ breast cancers. Clin Cancer Res; 22(13); 3249–59. ©2016 AACR.

Using transgenic mouse models, cell line-based functional studies, and clinical specimens, we show that cyclin D1/CDK4 mediate resistance to targeted therapy for HER2-positive breast cancer. This is overcome using CDK4/6 inhibitors. Inhibition of CDK4/6 not only suppresses Rb phosphorylation, but also reduces TSC2 phosphorylation and thus partially attenuates mTORC1 activity. This relieves feedback inhibition of upstream EGFR family kinases, resensitizing tumors to EGFR/HER2 blockade. Consequently, dual inhibition of EGFR/HER2 and CDK4/6 invokes a more potent suppression of TSC2 phosphorylation and hence mTORC1/S6K/S6RP activity. The suppression of both Rb and S6RP enhances G1 arrest and a phenotype resembling cellular senescence. In vivo, CDK4/6 inhibitors sensitize patient-derived xenograft tumors to HER2-targeted therapies and delay tumor recurrence in a transgenic model of HER2-positive breast cancer.

Item response theory (IRT), which originated from psychometric theory, relates to latent variable models for psychological assessment . IRT's contributions have been less extensively studied in cancer research even though IRT has become prevalent in the measurement of ability and item parameters with respect to latent traits. Benefits of IRT include comprehensive analyses and reduction of measurement error, meaningful scaling of latent variables, evaluation of test and item bias, greater accuracy in the assessment of change due to therapeutic intervention, and evaluation of model and person fit. Advances in cancer biology and human genetics have resulted in the identification of driver events and critical biologic dependencies. These advances, together with the development of drugs for specific biologic targets hold promise for an era of personalized oncology treatment. Therefore, robust discovery of biomarkers associated with the biologic mechanisms that drive cancers could provide clinicians with the ability to tailor therapeutic strategies for individual patients, thus improving clinical outcomes. Incorporating biomarkers in clinical trials during drug development may also allow for determining the optimal patient population for a given drug, thus maximizing its efficacy. Thus, this chapter explores the application of different IRT models in the discovery of biomarkers and altered biologic processes in cancer. The utility and limitations of the IRT models in the discovery of biomarkers or biological mechanisms are highlighted through simulations and application to genome-scale molecular profiling studies of cancers.

A clear contribution of the immune system to eradication of tumors has been supported by recent developments in the field of immunotherapy. Durable clinical responses obtained after treatment with immunomodulatory agents such as ipilimumab (Yervoy) and anti-PD-1 antibody (BMS-936558), have established that harnessing the immune response against chemoresistant tumors can result in their complete eradication. However, only a subset of patients benefit from these therapeutic approaches. Accumulating evidence suggests that tumors with a preexisting active immune microenvironment might have a better response to immunotherapy. In a number of preclinical and clinical studies, many cytotoxic agents elicit changes within tumors and their microenvironment that may make these malignant cells more sensitive to an efficient immune cell attack. Therefore, it is plausible that combining immunotherapy with standard anticancer therapies such as chemotherapy or radiotherapy will provide synergistic antitumor effects. Despite a large collection of preclinical data, the immune mechanisms that might contribute to the efficacy of conventional cytotoxic therapies and their combinations with immunotherapeutic approaches have not yet been extensively studied in the clinical setting and warrant further investigation. This review will focus on current knowledge of the immunomodulatory effects of one such cytotoxic treatment, radiotherapy, and explore different pathways by which its combination with immunomodulatory antibodies might contribute toward more efficacious antitumor immunity.

The HLA-F adjacent transcript 10 (FAT10) is a member of the ubiquitin-like gene family that alters protein function/stability through covalent ligation. Although FAT10 is induced by inflammatory mediators and implicated in immunity, the physiological functions of FAT10 are poorly defined. We report the discovery that FAT10 regulates lifespan through pleiotropic actions on metabolism and inflammation. Median and overall lifespan are increased 20% in FAT10ko mice, coincident with elevated metabolic rate, preferential use of fat as fuel, and dramatically reduced adiposity. This phenotype is associated with metabolic reprogramming of skeletal muscle (i.e., increased AMP kinase activity, β-oxidation and -uncoupling, and decreased triglyceride content). Moreover, knockout mice have reduced circulating glucose and insulin levels and enhanced insulin sensitivity in metabolic tissues, consistent with elevated IL-10 in skeletal muscle and serum. These observations suggest novel roles of FAT10 in immune metabolic regulation that impact aging and chronic disease.

Next‐generation sequencing (NGS) approaches for measuring RNA and DNA benefit from greatly increased sensitivity, dynamic range and detection of novel transcripts. These technologies are rapidly becoming the standard for molecular assays and represent huge potential value to the practice of oncology. However, many challenges exist in the transition of these technologies from research application to clinical practice. This review discusses the value of NGS in detecting mutations, copy number changes and RNA quantification and their applications in oncology, the challenges for adoption and the relevant steps that are needed for translating this potential to routine practice.

Treatment with histone deacetylase inhibitors (HDACI) results in potent cytotoxicity of a variety of cancer cell types, and these drugs are used clinically to treat hematological tumors. They are known to repress the transcription of ERBB2 and many other oncogenes, but little is known about this mechanism. Using global run-on sequencing (GRO-seq) to measure nascent transcription, we find that HDACI cause transcriptional repression by blocking RNA polymerase II elongation. Our data show that HDACI preferentially repress the transcription of highly expressed genes as well as high copy number genes in HER2+ breast cancer genomes. In contrast, genes that are activated by HDACI are moderately expressed. We analyzed gene copy number in combination with microarray and GRO-seq analysis of expression level, in normal and breast cancer cells to show that high copy number genes are more likely to be repressed by HDACI than non-amplified genes. The inhibition of transcription of amplified oncogenes, which promote survival and proliferation of cancer cells, might explain the cancer-specific lethality of HDACI, and may represent a general therapeutic strategy for cancer.