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Introduction This mixed methods study seeks to assess the clinical outcomes and qualitative insights associated with the pragmatic implementation of a general medicine (GM) physician-led inpatient care model, first at Alexandra Hospital (AH) and then at Sengkang General Hospital (SKH), and to compare them with findings reported in an earlier implementation of the family medicine (FM) hospitalist model in Singapore. Methods Anonymous quantitative demographic and clinical data including length of stay, 30-day readmission rate, inpatient mortality rate and gross cost of hospitalisation bills were extracted from the hospital information system. Comparative analyses with the FM hospitalist model and usual care were made. Secondary qualitative data that were gathered focused on increased understanding of the proposed model, its perceived challenges and future opportunities for its implementation. Results The adapted GM care model implemented first at AH and then at SKH seemed to suggest that such a model run by physicians from various backgrounds was capable of producing similarly superior outcomes when compared with the FM hospitalist model piloted in 2011, which was juxtaposed with usual care. With regard to qualitative insights, three findings were reported: (a) perception of and mindset in relation to generalists, which illustrates the barriers to implementing GM; (b) education and training of generalists, which underlines the current lack of adequate supply of GM specialists; and (c) operational issues of care model implementation, which highlights the current mismatches between the prevailing healthcare philosophy and the requirements for successful implementation of the GM care model. Conclusion The success of a GM care model hinges on how it is operationalised. With clear protocols, definitions, and a high level of protocol compliance by healthcare team members, the intended outcomes show promise for replication at other interested sites.

Lung cancer is the world’s leading cause of cancer death and shows strong ancestry disparities. By sequencing and assembling a large genomic and transcriptomic dataset of lung adenocarcinoma (LUAD) in individuals of East Asian ancestry (EAS; n = 305), we found that East Asian LUADs had more stable genomes characterized by fewer mutations and fewer copy number alterations than LUADs from individuals of European ancestry. This difference is much stronger in smokers as compared to nonsmokers. Transcriptomic clustering identified a new EAS-specific LUAD subgroup with a less complex genomic profile and upregulated immune-related genes, allowing the possibility of immunotherapy-based approaches. Integrative analysis across clinical and molecular features showed the importance of molecular phenotypes in patient prognostic stratification. EAS LUADs had better prediction accuracy than those of European ancestry, potentially due to their less complex genomic architecture. This study elucidated a comprehensive genomic landscape of EAS LUADs and highlighted important ancestry differences between the two cohorts. Genomic and transcriptomic analysis of lung adenocarcinoma (LUAD) in Asia indicates that Asian LUADs have fewer mutations, lower driver prevalence and fewer copy number alterations than European LUADs.

Simple Summary Metabolic adaptation by cancer cells is enabled through the rewiring of metabolic processes, thereby allowing them to survive and thrive in diverse tissue microenvironments. It is also exploited to maintain cancer stemness, drive epithelial–mesenchymal transition, and gain therapy resistance. These critical cellular events are pertinent to the various steps of cancer progression. Mechanistic insights into nutrient addiction arising from such metabolic rewiring have revealed therapeutic vulnerabilities that can be exploited as novel treatment modalities or for drug development. This review discusses concepts and principles of metabolic plasticity and highlights current preclinical and clinical strategies aimed at targeting these metabolic derangements. Abstract Cancer metabolism is a hallmark of cancer. Metabolic plasticity defines the ability of cancer cells to reprogram a plethora of metabolic pathways to meet unique energetic needs during the various steps of disease progression. Cell state transitions are phenotypic adaptations which confer distinct advantages that help cancer cells overcome progression hurdles, that include tumor initiation, expansive growth, resistance to therapy, metastasis, colonization, and relapse. It is increasingly appreciated that cancer cells need to appropriately reprogram their cellular metabolism in a timely manner to support the changes associated with new phenotypic cell states. We discuss metabolic alterations that may be adopted by cancer cells in relation to the maintenance of cancer stemness, activation of the epithelial–mesenchymal transition program for facilitating metastasis, and the acquisition of drug resistance. While such metabolic plasticity is harnessed by cancer cells for survival, their dependence and addiction towards certain metabolic pathways also present therapeutic opportunities that may be exploited.

Introduction Hospital-based practices today remain predominantly disease-oriented, focusing on individual clinical specialties with less visibility on a comprehensive picture of each patient’s health needs. To tackle the challenge of growing multimorbidity worldwide, practices without disease-specific focus have shown better integration of services. However, as we move away from the familiar disease-specific approaches of care delivery, many of us are still learning how to implement generalist care in a cost-effective manner. Methods This mixed-method case study, which centred on a specialist-led General Medicine model implemented at an acute hospital in Singapore, aimed to (1) quantitatively summarise its clinical outcomes, and (2) qualitatively describe the challenges and lessons gathered from the pragmatic implementation of the care model. Quantitative hospital data were extracted from databases and summarised. Qualitative staff-reported experiences and insights were gathered through semi-structured interviews and analysed using thematic analysis. Results Quantitative findings revealed that the generalist care model was implemented with high fidelity, where more than 75% of patients admitted were placed under General Medicine’s or General Surgery’s care. The mean length of stay was 2.6 days, and the 30-day post-discharge readmission rate was 15%. Inpatient mortality rate was found to be 2.8%, and the average gross hospitalisation bill amounted to SGD3,085.30. For qualitative findings, themes concerning feasibility and operational aspects of the implementation were grouped into categories- (1) Feasibility of ‘One Care Team’ approach, (2) Enablers required for meaningful generalist care, (3) Challenges surrounding information sharing, (4) Lack of integration with the community to facilitate care transition, and (5) Evolving roles of self-management. The findings were rich, with some being identified as barriers that could benefit from system-level de-constraining. Discussion This case study was an illustration of our pursuit for an integrated solution to rising prevalence of multimorbidity. While quantitative findings indicated that a pivot towards General Medicine might be possible, data also revealed gaps in clinical outcomes, especially in readmission rates. These findings corroborated with much of the lessons and challenges gathered from qualitative interviews, specifically surrounding the lack of receptacles in the community to facilitate care transition, training, and competency of generalists in holistic management of complex multimorbid cases, as well as inadequate infrastructure to allow information sharing between providers. Thus, a multi-pronged approach might be required to develop a new and sustainable care model for patients with multimorbidity in the long run. In the short to medium transitional period, nonetheless, the specialist-led General Medicine care model demonstrated might be a viable interim approach, especially in circumstances where trained medical generalists remained limited.

Lung cancer is the world's leading cause of cancer death and shows strong ancestry disparities. By sequencing and assembling a large genomic and transcriptomic dataset of lung adenocarcinoma (LUAD) in individuals of East Asian ancestry (EAS; n = 305), we found that East Asian LUADs had more stable genomes characterized by fewer mutations and fewer copy number alterations than LUADs from individuals of European ancestry. This difference is much stronger in smokers as compared to nonsmokers. Transcriptomic clustering identified a new EAS-specific LUAD subgroup with a less complex genomic profile and upregulated immune-related genes, allowing the possibility of immunotherapy-based approaches. Integrative analysis across clinical and molecular features showed the importance of molecular phenotypes in patient prognostic stratification. EAS LUADs had better prediction accuracy than those of European ancestry, potentially due to their less complex genomic architecture. This study elucidated a comprehensive genomic landscape of EAS LUADs and highlighted important ancestry differences between the two cohorts.

Lung cancer is the leading cause of cancer mortality globally, with lung adenocarcinoma being the most prevalent subtype. The discovery of driver mutations has paved the way for the use of targeted therapy, notably EGFR inhibitors, in the management of advanced disease. However, the effectiveness of targeted therapy is limited firstly by the eventual development of treatment resistance, and secondly by the sizeable percentage of cases in which the driver mutations remain unknown. Furthermore, lung adenocarcinoma (LUAD) in Asians is known to exhibit a molecular profile distinct from that in Caucasians, yet the majority of existing cohort studies have been focused on the latter. To address this gap, we and our collaborators have spearheaded the largest Asian LUAD cohort study, comprising genomic and transcriptomic data from 305 patients. The MutSigCV and 20/20+ driver prediction algorithms were applied to whole exome sequencing data from our cohort and yielded seven novel candidate drivers that had not been previously implicated in LUAD. We proceeded to functionally validate these drivers by overexpressing or knocking them down in patient-derived transformed lung cell lines and observing their effects on tumorigenicity via a number of in vitro and in vivo tumorigenicity assays. We have identified a poly (ADP-ribose) polymerase (PARP) gene, which was mutated at a relatively high frequency within our cohort, and show that PARP is crucial for modulating the tumorigenicity of lung cancer cells. In LUAD patients, reduced PARP expression levels were correlated with poorer prognosis, suggesting a putative tumor suppressor role. We further observed a loss of PARP copy number both within our cohort as well as the Caucasian The Cancer Genome Atlas (TCGA) LUAD cohort. We are now working to dissect the underlying mechanisms and explore PARP's clinical utility. This work illustrates the use of a platform to systematically model genetics in patient-derived models to study novel driver functions. Citation Format: Yi Fei Lee, Ju Yuan, Edwin Lim, Jianbin Chen, Weiwei Zhai, Nguan Soon Tan, Wai Leong Tam. Functionalizing novel modulators in lung cancer [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 291.