Questions to guide cancer evolution as a framework for furthering progress in cancer research and sustainable patient outcomes

MicroRNA-532 as a probable diagnostic and therapeutic marker in cancer patients

The high mortality rate in cancer patients is always one of the main challenges of the health systems globally. Several factors are involved in the high rate of cancer related mortality, including late diagnosis and drug resistance. Cancer is mainly diagnosed in the advanced stages of tumor progression that causes the failure of therapeutic strategies and increases the death rate in these patients. Therefore, assessment of the molecular mechanisms associated with the occurrence of cancer can be effective to introduce early tumor diagnostic markers. MicroRNAs (miRNAs) as the stable non-coding RNAs in the biological body fluids are involved in regulation of cell proliferation, migration, and apoptosis. MiR-532 deregulation has been reported in different tumor types. Therefore, in the present review we discussed the role of miR-532 during tumor growth. It has been shown that miR-532 has mainly a tumor suppressor role through the regulation of transcription factors, chemokines, and signaling pathways such as NF-kB, MAPK, PI3K/AKT, and WNT. In addition to the independent role of miR-532 in regulation of cellular processes, it also functions as a mediator of lncRNAs and circRNAs. Therefore, miR-532 can be considered as a non-invasive diagnostic/prognostic marker as well as a therapeutic target in cancer patients.

Tracking Karyotype Changes in Treatment-Induced Drug-Resistant Evolution

Karyotype coding, which encompasses the complete chromosome sets and their topological genomic relationships within a given species, encodes system-level information that organizes and preserves genes' function, and determines the macroevolution of cancer. This new recognition emphasizes the crucial role of karyotype characterization in cancer research. To advance this cancer cytogenetic/cytogenomic concept and its platforms, this study outlines protocols for monitoring the karyotype landscape during treatment-induced rapid drug resistance in cancer. It emphasizes four key perspectives: combinational analyses of phenotype and karyotype, a focus on the entire evolutionary process through longitudinal analysis, a comparison of whole landscape dynamics by including various types of NCCAs (including genome chaos), and the use of the same process to prioritize different genomic scales. This protocol holds promise for studying numerous evolutionary aspects of cancers, and it further enhances the power of karyotype analysis in cancer research.

The need for evolutionary theory in cancer research

Sir Richard Peto is well known for proposing puzzling paradoxes in cancer biology-some more well-known than others. In a 1984 piece, Peto proposed that after decades of molecular biology in cancer research, we are still ignorant of the biology underpinning cancer. Cancer is a product of somatic mutations. How do these mutations arise and what are the mechanisms? As an epidemiologist, Peto asked if we really need to understand mechanisms in order to prevent cancer? Four decades after Peto's proposed ignorance in cancer research, we can simply ask, are we still ignorant? Did the great pursuit to uncover mechanisms of cancer eclipse our understanding of causes and preventions? Or can we get closer to treating and preventing cancer by understanding the underlying mechanisms that make us most vulnerable to this disease?

Treatment of evolving cancers will require dynamic decision support

Cancer research has traditionally focused on developing new agents, but an underexplored question is that of the dose and frequency of existing drugs. Based on the modus operandi established in the early days of chemotherapies, most drugs are administered according to predetermined schedules that seek to deliver the maximum tolerated dose and are only adjusted for toxicity. However, we believe that the complex, evolving nature of cancer requires a more dynamic and personalized approach. Chronicling the milestones of the field, we show that the impact of schedule choice crucially depends on processes driving treatment response and failure. As such, cancer heterogeneity and evolution dictate that a one-size-fits-all solution is unlikely-instead, each patient should be mapped to the strategy that best matches their current disease characteristics and treatment objectives (i.e. their 'tumorscape'). To achieve this level of personalization, we need mathematical modeling. In this perspective, we propose a five-step 'Adaptive Dosing Adjusted for Personalized Tumorscapes (ADAPT)' paradigm to integrate data and understanding across scales and derive dynamic and personalized schedules. We conclude with promising examples of model-guided schedule personalization and a call to action to address key outstanding challenges surrounding data collection, model development, and integration.

Cracking the pattern of tumor evolution based on single-cell copy number alterations

Copy number alterations (CNAs) are a key characteristic of tumor development and progression. The accumulation of various CNAs during tumor development plays a critical role in driving tumor evolution. Heterogeneous clones driven by distinct CNAs have different selective advantages, leading to differential patterns of tumor evolution that are essential for developing effective cancer therapies. Recent advances in single-cell sequencing technology have enabled genome-wide copy number profiling of tumor cell populations at single-cell resolution. This has made it possible to explore the evolutionary patterns of CNAs and accurately discover the mechanisms of intra-tumor heterogeneity. Here, we propose a two-step statistical approach that distinguishes neutral, linear, branching and punctuated evolutionary patterns for a tumor cell population based on single-cell copy number profiles. We assessed our approach using a variety of simulated and real single-cell genomic and transcriptomic datasets, demonstrating its high accuracy and robustness in predicting tumor evolutionary patterns. We applied our approach to single-cell DNA sequencing data from 20 breast cancer patients and observed that punctuated evolution is the dominant evolutionary pattern in breast cancer. Similar conclusions were drawn when applying the approach to single-cell RNA sequencing data obtained from 132 various cancer patients. Moreover, we found that differential immune cell infiltration is associated with specific evolutionary patterns. The source code of our study is available at https://github.com/FangWang-SYSU/PTEM.

A synthetic lethal screen for Snail-induced enzalutamide resistance identifies JAK/STAT signaling as a therapeutic vulnerability in prostate cancer

Despite substantial improvements in the treatment landscape of prostate cancer, the evolution of hormone therapy-resistant and metastatic prostate cancer remains a major cause of cancer-related death globally. The mainstay of treatment for advanced prostate cancer is targeting of androgen receptor signaling, including androgen deprivation therapy plus second-generation androgen receptor blockade (e.g., enzalutamide, apalutamide, darolutamide), and/or androgen synthesis inhibition (abiraterone). While these agents have significantly prolonged the lives of patients with advanced prostate cancer, is nearly universal. This therapy resistance is mediated by diverse mechanisms, including both androgen receptor-dependent mechanisms, such as androgen receptor mutations, amplifications, alternative splicing, and amplification, as well as non-androgen receptor-mediated mechanisms, such as lineage plasticity toward neuroendocrine-like or epithelial-mesenchymal transition (EMT)-like lineages. Our prior work identified the EMT transcriptional regulator Snail as critical to hormonal therapy resistance and is commonly detected in human metastatic prostate cancer. In the current study, we sought to interrogate the actionable landscape of EMT-mediated hormone therapy resistant prostate cancer to identify synthetic lethality and collateral sensitivity approaches to treating this aggressive, therapy-resistant disease state. Using a combination of high-throughput drug screens and multi-parameter phenotyping by confluence imaging, ATP production, and phenotypic plasticity reporters of EMT, we identified candidate synthetic lethalities to Snail-mediated EMT in prostate cancer. These analyses identified multiple actionable targets, such as XPO1, PI3K/mTOR, aurora kinases, c-MET, polo-like kinases, and JAK/STAT as synthetic lethalities in Snail+ prostate cancer. We validated these targets in a subsequent validation screen in an LNCaP-derived model of resistance to sequential androgen deprivation and enzalutamide. This follow-up screen provided validation of inhibitors of JAK/STAT and PI3K/mTOR as therapeutic vulnerabilities for both Snail+ and enzalutamide-resistant prostate cancer.

Potential Role of the Fragile Histidine Triad in Cancer Evo-Dev

Cancer development follows an evolutionary pattern of "mutation-selection-adaptation" detailed by Cancer Evolution and Development (Cancer Evo-Dev), a theory that represents a process of accumulating somatic mutations due to the imbalance between the mutation-promoting force and the mutation-repairing force and retro-differentiation of the mutant cells to cancer initiation cells in a chronic inflammatory microenvironment. The fragile histidine triad (FHIT) gene is a tumor suppressor gene whose expression is often reduced or inactivated in precancerous lesions during chronic inflammation or virus-induced replicative stress. Here, we summarize evidence regarding the mechanisms by which the FHIT is inactivated in cancer, including the loss of heterozygosity and the promoter methylation, and characterizes the role of the FHIT in bridging macroevolution and microevolution and in facilitating retro-differentiation during cancer evolution and development. It is suggested that decreased FHIT expression is involved in several critical steps of Cancer Evo-Dev. Future research needs to focus on the role and mechanisms of the FHIT in promoting the transformation of pre-cancerous lesions into cancer.