Advances in Cancer Research最新文献

Current treatment of solid tumors with standard of care chemotherapies, radiation therapy and/or immunotherapies are often limited by severe adverse toxic effects, resulting in a narrow therapeutic index. Cancer gene therapy represents a targeted approach that in principle could significantly reduce undesirable side effects in normal tissues while significantly inhibiting tumor growth and progression. To be effective, this strategy requires a clear understanding of the molecular biology of cancer development and evolution and developing biological vectors that can serve as vehicles to target cancer cells. The advent and fine tuning of omics technologies that permit the collective and spatial recognition of genes (genomics), mRNAs (transcriptomics), proteins (proteomics), metabolites (metabolomics), epiomics (epigenomics, epitranscriptomics, and epiproteomics), and their interactomics in defined complex biological samples provide a roadmap for identifying crucial targets of relevance to the cancer paradigm. Combining these strategies with identified genetic elements that control target gene expression uncovers significant opportunities for developing guided gene-based therapeutics for cancer. The purpose of this review is to overview the current state and potential limitations in developing gene promoter-directed targeted expression of key genes and highlights their potential applications in cancer gene therapy.

Long noncoding RNAs (lncRNAs) comprise a diverse class of RNA molecules that regulate various physiological processes and have been reported to be involved in several human pathologies ranging from neurodegenerative disease to cancer. Therapeutic resistance is a major hurdle for cancer treatment. Over the past decade, several studies has emerged on the role of lncRNAs in cancer drug resistance and many trials have been conducted employing them. LncRNAs also regulate different cell death pathways thereby maintaining a fine balance of cell survival and death. Autophagy is a complex cell-killing mechanism that has both cytoprotective and cytotoxic roles. Similarly, autophagy can lead to the induction of both chemosensitization and chemoresistance in cancer cells upon therapeutic intervention. Recently the role of lncRNAs in the regulation of autophagy has also surfaced. Thus, lncRNAs can be used in cancer therapeutics to alleviate the challenges of chemoresistance by targeting the autophagosomal axis. In this chapter, we discuss about the role of lncRNAs in autophagy-mediated cancer drug resistance and its implication in targeted cancer therapy.

Underrepresented minority patients with pancreatic cancer have differential access to cancer treatments, including clinical trials. The successful conduct and completion of clinical trials is critical to improve outcomes for patients with pancreatic cancer. Therefore, it is essential to consider how to maximize eligibility of patients for both therapeutic and non-therapeutic clinical trials. It is important for clinicians and for the health system to understand individual-, clinician-, and system-level barriers to recruitment, enrollment, and completion of clinical trials to alleviate bias. Understanding strategies that lead to improved enrollment of underrepresented minorities, socioeconomically disadvantaged individuals, and underserved communities will improve generalizability of cancer clinical trials and advance health equity.

Hepatocellular carcinoma (HCC) risk prediction is increasingly important because of the low annual HCC incidence in patients with the rapidly emerging non-alcoholic fatty liver disease or cured HCV infection. To date, numerous clinical HCC risk biomarkers and scores have been reported in literature. However, heterogeneity in clinico-epidemiological context, e.g., liver disease etiology, patient race/ethnicity, regional environmental exposure, and lifestyle-related factors, obscure their real clinical utility and applicability. Proper characterization of these factors will help refine HCC risk prediction according to certain clinical context/scenarios and contribute to improved early HCC detection. Molecular factors underlying the clinical heterogeneity encompass various features in host genetics, hepatic and systemic molecular dysregulations, and cross-organ interactions, which may serve as clinical-context-specific biomarkers and/or therapeutic targets. Toward the goal to enable individual-risk-based HCC screening by incorporating the HCC risk biomarkers/scores, their assessment in patient with well-defined clinical context/scenario is critical to gauge their real value and to maximize benefit of the tailored patient management for substantial improvement of the poor HCC prognosis.

Biliary tract cancers (BTCs), which include cholangiocarcinoma (CCA) and gallbladder cancer (GBC), are heterogenous malignancies characterized by distinct molecular features often associated with specific clinical traits and/or outcomes. Such complex molecular heterogeneity, both within each BTC subtype and between distinct subtypes, poses a great challenge to personalized medicine. Recent technological advances have allowed the integration of multiple -omics derived from large cohorts of patients with distinct solid cancers to ultimately design stratification algorithms for prognostic prediction or more efficient treatment allocation. In this regard, although BTCs lag behind other tumors when it comes to our understanding of their molecular complexity, over the past decade, tremendous efforts have been made to generate supervised or unsupervised molecular classifications. As a result, CCAs and GBCs can be assigned to distinct molecular and/or prognostic classes. Notably, the discovery of biologically relevant subgroups of tumors harboring frequent targetable alterations (i.e., mutations in IDH1, FGFR2 fusion proteins) holds important therapeutic implications for BTCs, particularly iCCA. Furthermore, the recent application of single cell-based technologies or more conservative (and less precise) "virtual microdissection" algorithms to isolate signals derived from the immune and stromal cells has identified the first microenvironment-based classes. In this chapter, we will review the molecular and immune classes of BTCs, with a particular focus on their clinical implications.

Despite progress in treating or preventing viral hepatitis, a leading cause of liver cancer, hepatocellular cancer (HCC) continues to be a major cause of cancer-related deaths globally. HCC is a highly heterogeneous cancer with many genetic alterations common within a patient's tumor and between different patients. This complicates therapeutic strategies. In this review, we highlight the critical role that the Smad-mediated transforming growth factor β (TGF-β) pathway plays both in liver homeostasis and in the development and progression of HCC. We summarize the mouse models that have enabled the exploration of the dual nature of this pathway as both a tumor suppressor and a tumor promoter. Finally, we highlight how the insights gained from evaluating pathway activity using transcriptional profiling can be used to stratify HCC patients toward rational therapeutic regimens based on the differences in patients with early or late TGF-β pathway activity or activated, normal, or inactivated profiles of this key pathway.