Cancer treatment and research最新文献

As humanity continues to evolve, so do new treatments and the need to continually reevaluate and improve health care delivery. Cultural competency is at the core of improving health care delivery. However, cultural competency has proven to have limitations as it relates to the importance of on-going self-awareness, understanding, and consciousness of our own biases, culture, and values in the delivery of culturally sensitive patient and family-centric health care. The limited understanding of the true definition of cultural competency has hindered and blurred the guidelines on how to best communicate with patients and families throughout their care and end of life. With cultural humility, health care professionals can begin to lean into cultural confidence with resilience and curiosity.

The switch/sucrose non-fermenting (SWI/SNF) chromatin remodeling complex is a global regulator of gene expression known to maintain nucleosome-depleted regions at active enhancers and promoters. The mammalian SWI/SNF protein subunits are encoded by 29 genes and 11-15 subunits including an ATPase domain of either SMARCA4 (BRG1) or SMARCA2 (BRM) are assembled into a complex. Based on the distinct subunits, SWI/SNF are grouped into 3 major types (subfamilies): the canonical BRG1/BRM-associated factor (BAF/cBAF), polybromo-associated BAF (PBAF), and non-canonical BAF (GBAF/ncBAF). Pan-cancer genome sequencing studies have shown that nearly 25% of all cancers bear mutations in subunits of the SWI/SNF complex, many of which are loss of function (LOF) mutations, suggesting a tumor suppressor role. Inactivation of SWI/SNF complex subunits causes widespread epigenetic dysfunction, including increased dependence on antagonistic components such as polycomb repressor complexes (PRC1/2) and altered enhancer regulation, likely promoting an oncogenic state leading to cancer. Despite the prevalence of mutations, most SWI/SNF-mutant cancers lack targeted therapeutic strategies. Defining the dependencies created by LOF mutations in SWI/SNF subunits will identify better targets for these cancers.

The impact of nutritional patterns on the risk of breast cancer (BC) is well investigated in the oncology literature, including the type of diets and caloric intake. While obesity and elevated body mass index are well-reported critical risk factors of BC occurrence, there is an expanding area of oncology assessing the impact of caloric intake and nutritional patterns in patients with cancer. Caloric restriction and fast mimicking alimentary regimens have been consistently reported to improve survival outcomes based on preclinical models. Moreover, emerging clinical evidence has paved the way for new metabolic approaches for the treatment of BC, in addition to the established therapeutic arsenal or as alternative options. In this chapter, our aim is to discuss the principal strategies of metabolic manipulation through nutritional interventions for patients with BC as an innovative area of cancer therapy.

The hormonal therapy for cancer has become a household name and the series of experiments performed leading to the discovery of hormones use in the treatments of breast cancer. The hormones like antiestrogen, aromatase restrictors, antiandrogens, and use of extremely strong luteinizing hormone-releasing hormone agonists to perform a "medical hypophysectomy" because of their ability of causing desensitization in the pituitary gland have proven their value in the treatment of cancers over the last two decades. Millions of women still use hormonal therapy for menopause symptoms. Estrogen plus progestin or estrogen separately utilized as a menopause hormonal therapy throughout the world. Women receiving different premenopausal and postmenopausal hormonal therapies are on higher risk of having ovarian cancer. The risk of ovarian cancer did not increase with the increase of duration of hormonal therapy. Postmenopausal hormone use was found to be inversely related to major colorectal adenomas.

Targeted therapy and personalized medicine are novel emerging disciplines of cancer research intended for treatment and prevention. One of the most significant advancements in modern oncology is the shift from an organ-centric strategy to a personalized strategy guided by deep molecular analysis. This shift in view, which focuses on the tumour's precise molecular changes, has paved the way for individualized treatment. Researchers and clinicians are using targeted therapies to select the best treatment available based on the molecular characterization of malignant cancer. In the treatment of a cancer, personalized medicine entails the use of genetic, immunological, and proteomic profiling to provide therapeutic alternatives as well as prognostic information about cancer. In this book, targeted therapies and personalized medicine have been covered for specific malignancies, including latest FDA-approved targeted therapies and it also sheds light on effective anti-cancer regimens and drug resistance. This will help to enhance our ability to conduct individualized health planning, make early diagnoses, and choose optimal medications for each cancer patient with predictable side effects and outcomes in a quickly evolving era. Various applications and tools' capacity have been improved for early diagnosis of cancer and the growing number of clinical trials that choose specific molecular targets reflects this predicament. Nevertheless, there are several limitations that must need to be addressed. Hence, in this chapter, we will discuss recent advancements, challenges, and opportunities in personalized medicine for various cancers, with a specific emphasis on target therapies in diagnostics and therapeutics.

Cancer is a complex disease. According to the Globocan survey, 63% deaths are due to cancer. There are some conventional methods that are used to treat cancer. However, certain treatment modalities are under clinical trials still. The success of treatment depends on type and stage of cancer, locality, and patient's response to that specific treatment. Most widely used treatments are surgery, radiotherapy, and chemotherapy. Personalized treatment approach has some promising effects, yet some of the points are still unclear. This chapter has provided the overview of some of the therapeutic modalities; however, the therapeutic potential has been discussed in details throughout the book.

In this chapter, we illustrate how evidence about treatments' benefits and harms can be integrated to enable rational decision-making even under considerable clinical uncertainty.

In this chapter, we discuss the potential role that artificial intelligence (AI) may have in medical decision-making, the pros and cons, and the limitations and biases that might be introduced when using these novel techniques. As computing becomes more powerful and models continue to grow increasingly more complex, the potential of AI to improve decision-making is increasingly promising. Within many medical fields, however, at the time of this writing (September 2023), the promise of AI is yet to translate into everyday reality. Here, we summarize the role of AI in medical decision-making (diagnosis, prognosis, and treatment).

Neoadjuvant treatments (NAT) for breast cancer (BC) consist in the administration of chemotherapy-more rarely endocrine therapy-before surgery. Firstly, it was introduced 50 years ago to downsize locally advanced (inoperable) BCs. NAT are now widespread and so effective to be used also at the early stage of the disease. NAT are heterogeneous in terms of therapeutic patterns, class of used drugs, dosage, and duration. The poly-chemotherapy regimen and administration schedule are established by a multi-disciplinary team, according to the stage of disease, the tumor subtype and the age, the physical status, and the drug sensitivity of BC patients. Consequently, an accurate monitoring of treatment response can provide significant clinical advantages, such as the treatment de-escalation in case of early recognition of complete response or, on the contrary, the switch to an alternative treatment path in case of early detection of resistance to the ongoing therapy. Future is going toward increasingly personalized therapies and the prediction of individual response to treatment is the key to practice customized care pathways, preserving oncological safety and effectiveness. To gain such goal, the development of an accurate monitoring system, reproducible and reliable alone or as part of more complex diagnostic algorithms, will be promising.

The rapid implementation of precision medicine tools in diagnosing and treating breast cancer (BC) has widened the potential therapeutic options for patients. The applications of gene sequencing, including next-generation gene sequencing (NGS), have led to numerous questions on how to validate, implement, interpret, prioritize and operationalize precision medicine tools to deliver meaningful and impactful interventions. Limited benefit has been portended with earlier experiences of NGS-driven treatment, in BC. However, the development and use of frameworks of clinical actionability of genomic alterations, for example, detected with NGS, has resulted in better patient selection, and potentially higher therapeutic value. The European Society for Medical Oncology Scale for Clinical Actionability of molecular Targets (ESCAT) is a framework that includes five tiers of clinical actionability, with tier 1 reserved for approved drugs with demonstrated benefits for targetable genomic alterations. The re-analysis of clinical studies by grouping the genomic alterations and matched drugs with ESCAT, in high vs lower tiers has demonstrated a significant benefit portended by high tiers alterations, with the availability of efficacious treatments. As a result, frameworks for actionability, like ESCAT, should be fundamental in developing and implementing NGS-driven, and broadly, precision medicine research and treatments.