The road map of cancer precision medicine with the innovation of advanced cancer detection technology and personalized immunotherapy

Big data in breast cancer: Towards precision treatment

Breast cancer is the most prevalent and deadliest cancer among women globally, representing a major threat to public health. In response, the World Health Organization has established the Global Breast Cancer Initiative framework to reduce breast cancer mortality through global collaboration. The integration of big data analytics (BDA) and precision medicine has transformed our understanding of breast cancer's biological traits and treatment responses. By harnessing large-scale datasets - encompassing genetic, clinical, and environmental data - BDA has enhanced strategies for breast cancer prevention, diagnosis, and treatment, driving the advancement of precision oncology and personalised care. Despite the increasing importance of big data in breast cancer research, comprehensive studies remain sparse, underscoring the need for more systematic investigation. This review evaluates the contributions of big data to breast cancer precision medicine while addressing the associated opportunities and challenges. Through the application of big data, we aim to deepen insights into breast cancer pathogenesis, optimise therapeutic approaches, improve patient outcomes, and ultimately contribute to better survival rates and quality of life. This review seeks to provide a foundation for future research in breast cancer prevention, treatment, and management.

Cancer Prevalence Projections in Japan and Decomposition Analysis of Changes in Cancer Burden, 2020-2050: A Statistical Modeling Study

BACKGROUND

We provide comprehensive sex-stratified projections of cancer prevalence for 22 cancer sites in Japan from 2020 to 2050.

METHODS

Using a scenario-based approach, we projected cancer prevalence by combining projected incidence cases and survival probabilities. Age-specific incidences were forecasted using age-period-cohort models, while survival rates were estimated using a period-analysis approach and multiple parametric survival models. To understand changes in cancer prevalence, decomposition analysis was conducted, assessing the contributions of incidence, survival, and population demographics.

RESULTS

By 2050, cancer prevalence in Japan is projected to reach 3,665,900 (3,210,200 to 4,201,400) thousand cases, representing a 13.1% increase from 2020. This rise is primarily due to a significant increase in female survivors (+27.6%) compared with a modest increase in males (+0.8%), resulting in females overtaking males in prevalence counts from 2040 onward. In 2050, the projected most prevalent cancer sites in Japan include colorectal, female breast, prostate, lung, and stomach cancers, accounting for 66.4% of all survivors. Among males, the highest absolute increases in prevalence are projected for prostate, lung, and malignant lymphoma cancers, while among females, the highest absolute increases are expected for female breast, colorectal, and corpus uteri cancers.

CONCLUSIONS

These findings emphasize the evolving cancer prevalence, influenced by aging populations, changes in cancer incidence rates, and improved survival. Effective prevention, detection, and treatment strategies are crucial to address the growing cancer burden.

IMPACT

This study contributes to comprehensive cancer control strategies and ensures sufficient support for cancer survivors in Japan.

Development of artificial intelligence technology in diagnosis, treatment, and prognosis of colorectal cancer

Artificial intelligence (AI) technology has made leaps and bounds since its invention. AI technology can be subdivided into many technologies such as machine learning and deep learning. The application scope and prospect of different technologies are also totally different. Currently, AI technologies play a pivotal role in the highly complex and wide-ranging medical field, such as medical image recognition, biotechnology, auxiliary diagnosis, drug research and development, and nutrition. Colorectal cancer (CRC) is a common gastrointestinal cancer that has a high mortality, posing a serious threat to human health. Many CRCs are caused by the malignant transformation of colorectal polyps. Therefore, early diagnosis and treatment are crucial to CRC prognosis. The methods of diagnosing CRC are divided into imaging diagnosis, endoscopy, and pathology diagnosis. Treatment methods are divided into endoscopic treatment, surgical treatment, and drug treatment. AI technology is in the weak era and does not have communication capabilities. Therefore, the current AI technology is mainly used for image recognition and auxiliary analysis without in-depth communication with patients. This article reviews the application of AI in the diagnosis, treatment, and prognosis of CRC and provides the prospects for the broader application of AI in CRC.

Leveraging advances in immunopathology and artificial intelligence to analyze in vitro tumor models in composition and space

Cancer is the leading cause of death worldwide. Unfortunately, efforts to understand this disease are confounded by the complex, heterogenous tumor microenvironment (TME). Better understanding of the TME could lead to novel diagnostic, prognostic, and therapeutic discoveries. One way to achieve this involves in vitro tumor models that recapitulate the in vivo TME composition and spatial arrangement. Here, we review the potential of harnessing in vitro tumor models and artificial intelligence to delineate the TME. This includes (i) identification of novel features, (ii) investigation of higher-order relationships, and (iii) analysis and interpretation of multiomics data in a (iv) holistic, objective, reproducible, and efficient manner, which surpasses previous methods of TME analysis. We also discuss limitations of this approach, namely inadequate datasets, indeterminate biological correlations, ethical concerns, and logistical constraints; finally, we speculate on future avenues of research that could overcome these limitations, ultimately translating to improved clinical outcomes.

Clinical implementation and current advancement of blood liquid biopsy in cancer

Liquid biopsies have been receiving tremendous attentions as easy, rapid, and non-invasive tools for cancer diagnosis. Liquid biopsy can be performed repeatedly for disease monitoring and is expected to overcome the limitations of tissue biopsies. With the advancement of next generation sequencing technologies, it is now possible to detect minute amount of tumor-derived circulation tumor DNA (ctDNA) from blood samples. Importantly, ctDNA detection could be complementary to tissue biopsies or tumor biomarkers particularly in cases of which tumor biopsy is clinically difficult to obtain. Here, we introduce the up-to-date technologies used in cfDNA-based liquid biopsy and review the clinical utilities of ctDNA in cancer screening, detection of minimal residual diseases, selection of molecular-targeted drugs, as well as monitoring of treatment responsiveness. We also discuss the challenges and future perspectives of liquid biopsy implementation in clinical setting.

Recent developments in antibody derivatives against colorectal cancer; A review

Colorectal cancer (CRC) is the fourth most common cause of cancer and mortality worldwide and is the third most common cancer in men and women. Surgery, radiotherapy, and chemotherapy are conventionally used for the treatment of colorectal cancer. However, these methods are associated with various side effects on normal cells. Thus, new studies are moving towards more effective and non-invasive methods for treatment of colorectal cancer. Targeted therapy of CRC is a promising new approach to enhance the efficiency and decrease the toxicity of the treatment. In targeted therapy of CRC, antibody fragments can directly inhibit tumor cell growth and proliferation. They also can act as an ideal carrier for targeted delivery of anticancer drugs. In the present study, the structure and function of different formats of antibody fragments, immune-targeted therapy of CRC using antibody fragments will be discussed.

Are Pathogenic Germline Variants in Metastatic Melanoma Associated with Resistance to Combined Immunotherapy?

Background: Combined immunotherapy has significantly improved survival of patients with advanced melanoma, but there are still patients that do not benefit from it. Early biomarkers that indicate potential resistance would be highly relevant for these patients. Methods: We comprehensively analyzed tumor and blood samples from patients with advanced melanoma, treated with combined immunotherapy and performed descriptive and survival analysis. Results: Fifty-nine patients with a median follow-up of 13 months (inter quartile range (IQR) 11–15) were included. Interestingly, nine patients were found to have pathogenic or likely pathogenic (P/LP) germline variants in one of these genes: BRCA2, POLE, WRN, FANCI, CDKN2A, BAP1, PALB2 and RAD54B. Most of them are involved in DNA repair mechanisms. Patients with P/LP germline variants had a significantly shorter progression-free survival (PFS) and melanoma specific survival (MSS) compared to patients without P/LP germline variants (HR = 2.16; 95% CI: 1.01–4.64; p = 0.048 and HR = 3.21; 95% CI: 1.31–7.87; p = 0.011, respectively). None of the patients with a P/LP germline variant responded to combined immunotherapy. In the multivariate Cox-regression analysis, presence of a P/LP germline variant, S100B and lactate dehydrogenase (LDH) remained independently significant factors for MSS (p = 0.036; p = 0.044 and p = 0.001, respectively). Conclusions: The presence of P/LP germline variants was associated with resistance to combined immunotherapy in our cohort. As genes involved in DNA repair mechanisms are also involved in lymphocyte development and T-cell differentiation, a P/LP germline variant in these genes may preclude an antitumor immune response.